To beat the issues arising owing to transients , these are required to be suppressed . In this paper , an easy and economical techniquie is conferred to limit the transient current of the Y-yg transformers . One amongst the most benefit of this technique is it does n’t would like any negative feedback circuit or activity unit . While it is relatively easy to compute and measure the power losses in semiconductor devices , it is practically difficult to measure the power losses in magnetic components . The data sheets provided by the manufacturers , for core loss and thermal resistance , do act as a starting point in the design stage but , always the designers felt the need to know the exact power loss in the ferrite high frequency transformers and their thermal resistance values . The data sheets provide thermal resistance values only for the cores and it is necessary to quantify value for a fully wound transformers . Distribution-connected inverter-based distributed energy resources ( DERs ) plants can under certain circumstances contribute to transient overvoltages . System operators often require the use of grounding transformers with such plants as an overvoltage mitigation strategy . In this paper , a set of grounding transformer design relationships is derived from the sequence network representation of a distribution circuit hosting a DER with a grounding transformer . The proposed approach draws sinusoidal input current at unity power factor and has output voltage regulation capability . The size and weight of the magnetic devices is reduced since a low-kilovolt-ampere three-phase autotransformer is incorporated and dc outputs of two bridges are directly connected without using low-frequency interphase transformers ( IPTs ) . The methodology makes use of the thin wire models of CST , which are well suited to represent the high voltage bus bars and cables connecting the 3-dimensional structures of the converter valves and halls . Additional key components such as grid transformers and phase reactors are included as hybrid models , consisting of 3-dimensional structures in combination with imported circuit netlists . The converter itself is modeled as impulse sources in the CST circuit schematic , where the switching pulse patterns and the cell switching characteristics are taken into account in a final post-processing step in combination with electromagnetic interference ( EMI ) detector models . The basic principles of ' transformer analogue computation1 first suggested by Blackburn ( 1937 ) , have been extended to yield a compact , accurate and inexpensive computer for the solution of algebraic equations . The computer uses only tapped transformers and ganged switches as its building elements . A unique feature of the computer is that coefficients greater than unity can be set very easily , thereby increasing the accuracy to which a root can be evaluated . It has been proven that the interwindings capacitance introduced by close conductors of each winding , evaluated to 13 pF , assures the most important role in the power transfer . This article has shown that by optimizing properly the transformer realization and limiting some parasitics elements , the inductive and capacitive links could both play a key role in MEMS transducers through tapped transformers operation around 100-kHz frequencies . The invention discloses a traction transformation device . The device comprises a plurality of cascaded sub-transformers and a plurality of bypass switches corresponding to the sub-transformers . The invention also discloses a traction transformation method . In this research , a model has been developed to characterize the behavior of LED lighting systems for airfield applications . The model includes the saturated dynamics of isolation transformers , a distributed representation of the airfield cable , diode rectification , and the dynamics of a current-regulated isolated power supply . Herein the details of the model , including its validation , are first described . System and method for providing real-time distribution feeder automation system for load balancing reconfiguration . Feeder transformers and load balancing is achieved by means of a transformer from an overloaded load transfer feeder or a light load to an adjacent transformer or feeder . The method includes defining an objective function transformer / feeding load deviation and the square of the electric wire . A complete model of this HVDC BtB has been developed by the authors with ATP ( Alternative Transients Program ) for conducting power system electromagnetic transient ( EMT ) simulations . In relation to the work carried out , this paper presents the following issues : the main technical characteristics of the HVDC BtB , the Static Characteristic under normal and abnormal operating conditions and control loops associated , bridge converter and thyristor firing scheme modelling , power converter transformers modelling , temporary over/under voltage control , initialization of the back-to-back model , application and removal of balanced three-phase fault at both rectifier and inverter sides , single phase fault with successful auto-reclosure at Uruguay side . In order to evaluate the ATP model the simulation results were compared against PSCAD and RTDS results given by the manufacturer . For instance , spatial transformer networks were initially shown to facilitate image classification by transforming images onto the same frame of reference . Recently , it has been shown how spatial transformers can encode optical flow features with unsupervised training , but they have nevertheless not yet been investigated for video motion compensation . Related approaches have emerged for view synthesis assuming rigid transformations . Transformer-based models are unable to process long sequences due to their self-attention operation , which scales quadratically with the sequence length . To address this limitation , we introduce the Longformer with an attention mechanism that scales linearly with sequence length , making it easy to process documents of thousands of tokens or longer . Longformer 's attention mechanism is a drop-in replacement for the standard self-attention and combines a local windowed attention with a task motivated global attention . Following prior work on long-sequence transformers , we evaluate Longformer on character-level language modeling and achieve state-of-the-art results on text8 and enwik8 . In contrast to most prior work , we also pretrain Longformer and finetune it on a variety of downstream tasks . Our pretrained Longformer consistently outperforms RoBERTa on long document tasks and sets new state-of-the-art results on WikiHop and TriviaQA . Based on the topology structure , grounding method , main equipment parameters , load parameters and system control protection strategy of the DC power distribution system , this paper establishes the system simulation model in the case of configuring the connection transformer and not configuring the connection transformer . Simulation results show that , when no connecting transformer is installed , the interaction between AC and DC systems will be great when faults occur , and the cost of converter valves and DC reactors will be increased . When connecting transformers are installed , the interaction between AC and DC systems can be effectively isolated , and the operation reliability of the system will be greatly improved while the cost is saved . Automatic on-load voltage regulation of transformer is an effective method to stabilize load voltage . Mechanic contact tap changing switch is not adequate for distributing transformer because of its high cost and low capability . The paper presents the structure and automatic on-load voltage regulating principle of distributing transformer which employs solid state relay as non contact automatic on-load voltage regulat-ing tap changing switch . The utility model discloses a protection system capable of realizing breaker failure triggering relevant trips of an interconnecting transform . The protection system analyzes the reasons that : if the circuit breaker on any one side is in failure , not all relevant trips of the circuit breakers on the power supply side are triggered , and the 220kV side breaker failure protection logic of the interconnecting transformer is changed , and the function of the breaker failure triggering relevant trips for interconnecting transformer protection is truly realized , and the technical regulation requirements is achieved , and guarantees on safe and stable operation of the power grid are supplied . The IP camera adopts the technical scheme that a video collection device , a processor with a built-in video encoder and a built-in video decoder , a local display device and an FEC ( forward error correction ) interface circuit are comprised . The processor adopts i. MX27 ; the CSI ( Chinese system interface ) interface of the processor is connected with the video collection device ; an LCDC interface is connected with the local display device ; and the FEC interface is connected with the Ethernet through the FEC interface circuit and a network transformer in sequence . The IP camera istaken as a server ; client ( can be a computer device or a 3 G mobile phone ) is permitted to visit the camera through network ; the audio-frequency calling from the client is received by the camera ; and only by turning on the TV , voice communication and video communication with the client can be achieved . This work builds upon two lines of research : it combines the modeling flexibility of prior work on content-based sparse attention with the efficiency gains from approaches based on local , temporal sparse attention . Our model , the Routing Transformer , endows self-attention with a sparse routing module based on online k-means while reducing the overall complexity of attention to $ O\left(n^{1.5}d\right)$ from $ O\left(n^2d\right)$ for sequence length $ n$ and hidden dimension $ d$. We show that our model outperforms comparable sparse attention models on language modeling on Wikitext-103 ( 15.8 vs 18.3 perplexity ) as well as on image generation on ImageNet-64 ( 3.43 vs 3.44 bits/dim ) while using fewer self-attention layers . This paper describes the development of a compact n/8 inductive voltage divider ( IVD ) for the use in the frequency range between 1 and 100 kHz and voltages up to 5 V. The development includes a number of additional inductive components for the bootstrap calibration setup such as a supply transformer which ensures the galvanic isolation of the calibration setup , a calibration transformer , and a detection transformer . The desired frequency and uncertainty range requires a two-stage IVD design with coaxial windings , a triaxial differential branch , and voltage controlled shields to minimize capacitive stray currents . This paper proposes a versatile convertible static transmission controller , in shunt-shunt mode , with dual active filters and photovoltaic ( PV ) power integration . The combined system aims to back up and control the power of a transmission transformer , as well as , improve the transmitted power quality to meet the grid standards and codes , especially the recently revised IEEE 1547 standards . The filters are also designed to eliminate the current and voltage harmonics due to the fluctuation in the injected PV power and the use of the switching power converters . Usually the STN computes one affine transform for the whole image , considering a pedestrian ’s different parts have various orientations and sizes from each other , STN is not applicable to a part image . Inspired by STN , we design a Pose Transformer Network ( PTN ) which computes the affine transformation for each part in part image individually and combines 6 transformed parts together . Similar to STN , our PTN is also a small net and does n’t substantially increase the complexity of our training procedure . document : Weighted Transformer Network for Machine Translation State - of - the - art results on neural machine translation often use attentional sequence - to - sequence models with some form of convolution or recursion . Coreference resolution has been an active field of research in the past several decades and plays a vital role in many areas such as information extraction , document summarization , machine translation , and question answering systems . This paper presents a new coreference resolution approach by incorporating RoBERTa embedding with a neural multi-criteria decision making ( MCDM ) method . The proposed model does not use any syntactic and dependency parser . Experimental results on these datasets show that the whole word masking could bring another significant gain . Moreover , we also examine the effectiveness of the Chinese pre-trained models : BERT , ERNIE , BERT-wwm , BERT-wwm-ext , RoBERTa-wwm-ext , and RoBERTa-wwm-ext-large . We release all the pre-trained models : \url{this https URL Further approaches can be found in current literature . For instance , the Roberta Initiative ( raising girl ’s interest in technical topics ) conducted teacher training courses ( including certification ) only in robotics applying a train-the-trainer concept . ( Bredenfeld and Leimbach 2010 ) . In our study , we used English BERT ( En-BERT ) , RoBERTa , DistilRoBERTa , and SVM based classifiers for the English language . For Hindi and Bangla language , multilingual BERT ( M-BERT ) , XLM-RoBERTa and SVM classifiers were used . Our best performing models are EN-BERT for English Subtask A ( Weighted F1 score of 0.73 , Rank 5/16 ) , SVM for English Subtask B ( Weighted F1 score of 0.87 , Rank 2/15 ) , SVM for Hindi Subtask A ( Weighted F1 score of 0.79 , Rank 2/10 ) , XLMRoBERTa for Hindi Subtask B ( Weighted F1 score of 0.87 , Rank 2/10 ) , SVM for Bangla Subtask A ( Weighted F1 score of 0.81 , Rank 2/10 ) , and SVM for Bangla Subtask B ( Weighted F1 score of 0.93 , Rank 4/8 ) . Interpretation based Verification of Logic Programs Marco Comini , Roberta Gori , Giorgio Levi , Paolo Volpe Dipartimento di Informatica Università di Pisa Pisa , Italy We further introduce new fine-tuning objectives to improve in-domain unsupervised fine-tuning to better utilize large amount of unlabeled in-domain data . We experiment on real world invoice and resume data sets and show that the proposed method outperforms strong text-based RoBERTa baselines by 6.3 % absolute F1 on invoices and 4.7 % absolute F1 on resumes . When evaluated in a few-shot setting , our method requires up to 30x less annotation data than the baseline to achieve the same level of performance at ~90 % F1 . Methods We proposed a classifier for short text eligibility criteria based on ensemble learning , where a set of pretrained models was integrated . The pretrained models included state-of-the-art deep learning methods for training and classification , including Bidirectional Encoder Representations from Transformers ( BERT ) , XLNet , and A Robustly Optimized BERT Pretraining Approach ( RoBERTa ) . The classification results by the integrated models were combined as new features for training a Light Gradient Boosting Machine ( LightGBM ) model for eligibility criteria classification .
To beat the issues arising owing to transients , these are required to be suppressed . In this paper , an easy and economical techniquie is conferred to limit the transient current of the Y-yg transformers . One amongst the most benefit of this technique is it does n’t would like any negative feedback circuit or activity unit .
While it is relatively easy to compute and measure the power losses in semiconductor devices , it is practically difficult to measure the power losses in magnetic components . The data sheets provided by the manufacturers , for core loss and thermal resistance , do act as a starting point in the design stage but , always the designers felt the need to know the exact power loss in the ferrite high frequency transformers and their thermal resistance values . The data sheets provide thermal resistance values only for the cores and it is necessary to quantify value for a fully wound transformers .
Distribution-connected inverter-based distributed energy resources ( DERs ) plants can under certain circumstances contribute to transient overvoltages . System operators often require the use of grounding transformers with such plants as an overvoltage mitigation strategy . In this paper , a set of grounding transformer design relationships is derived from the sequence network representation of a distribution circuit hosting a DER with a grounding transformer .
The proposed approach draws sinusoidal input current at unity power factor and has output voltage regulation capability . The size and weight of the magnetic devices is reduced since a low-kilovolt-ampere three-phase autotransformer is incorporated and dc outputs of two bridges are directly connected without using low-frequency interphase transformers ( IPTs ) .
The methodology makes use of the thin wire models of CST , which are well suited to represent the high voltage bus bars and cables connecting the 3-dimensional structures of the converter valves and halls . Additional key components such as grid transformers and phase reactors are included as hybrid models , consisting of 3-dimensional structures in combination with imported circuit netlists . The converter itself is modeled as impulse sources in the CST circuit schematic , where the switching pulse patterns and the cell switching characteristics are taken into account in a final post-processing step in combination with electromagnetic interference ( EMI ) detector models .
The basic principles of ' transformer analogue computation1 first suggested by Blackburn ( 1937 ) , have been extended to yield a compact , accurate and inexpensive computer for the solution of algebraic equations . The computer uses only tapped transformers and ganged switches as its building elements . A unique feature of the computer is that coefficients greater than unity can be set very easily , thereby increasing the accuracy to which a root can be evaluated .
It has been proven that the interwindings capacitance introduced by close conductors of each winding , evaluated to 13 pF , assures the most important role in the power transfer . This article has shown that by optimizing properly the transformer realization and limiting some parasitics elements , the inductive and capacitive links could both play a key role in MEMS transducers through tapped transformers operation around 100-kHz frequencies .
The invention discloses a traction transformation device . The device comprises a plurality of cascaded sub-transformers and a plurality of bypass switches corresponding to the sub-transformers . The invention also discloses a traction transformation method .
In this research , a model has been developed to characterize the behavior of LED lighting systems for airfield applications . The model includes the saturated dynamics of isolation transformers , a distributed representation of the airfield cable , diode rectification , and the dynamics of a current-regulated isolated power supply . Herein the details of the model , including its validation , are first described .
System and method for providing real-time distribution feeder automation system for load balancing reconfiguration . Feeder transformers and load balancing is achieved by means of a transformer from an overloaded load transfer feeder or a light load to an adjacent transformer or feeder . The method includes defining an objective function transformer / feeding load deviation and the square of the electric wire .
A complete model of this HVDC BtB has been developed by the authors with ATP ( Alternative Transients Program ) for conducting power system electromagnetic transient ( EMT ) simulations . In relation to the work carried out , this paper presents the following issues : the main technical characteristics of the HVDC BtB , the Static Characteristic under normal and abnormal operating conditions and control loops associated , bridge converter and thyristor firing scheme modelling , power converter transformers modelling , temporary over/under voltage control , initialization of the back-to-back model , application and removal of balanced three-phase fault at both rectifier and inverter sides , single phase fault with successful auto-reclosure at Uruguay side . In order to evaluate the ATP model the simulation results were compared against PSCAD and RTDS results given by the manufacturer .
For instance , spatial transformer networks were initially shown to facilitate image classification by transforming images onto the same frame of reference . Recently , it has been shown how spatial transformers can encode optical flow features with unsupervised training , but they have nevertheless not yet been investigated for video motion compensation . Related approaches have emerged for view synthesis assuming rigid transformations .
Transformer-based models are unable to process long sequences due to their self-attention operation , which scales quadratically with the sequence length . To address this limitation , we introduce the Longformer with an attention mechanism that scales linearly with sequence length , making it easy to process documents of thousands of tokens or longer . Longformer 's attention mechanism is a drop-in replacement for the standard self-attention and combines a local windowed attention with a task motivated global attention . Following prior work on long-sequence transformers , we evaluate Longformer on character-level language modeling and achieve state-of-the-art results on text8 and enwik8 . In contrast to most prior work , we also pretrain Longformer and finetune it on a variety of downstream tasks . Our pretrained Longformer consistently outperforms RoBERTa on long document tasks and sets new state-of-the-art results on WikiHop and TriviaQA .
Based on the topology structure , grounding method , main equipment parameters , load parameters and system control protection strategy of the DC power distribution system , this paper establishes the system simulation model in the case of configuring the connection transformer and not configuring the connection transformer . Simulation results show that , when no connecting transformer is installed , the interaction between AC and DC systems will be great when faults occur , and the cost of converter valves and DC reactors will be increased . When connecting transformers are installed , the interaction between AC and DC systems can be effectively isolated , and the operation reliability of the system will be greatly improved while the cost is saved .
Automatic on-load voltage regulation of transformer is an effective method to stabilize load voltage . Mechanic contact tap changing switch is not adequate for distributing transformer because of its high cost and low capability . The paper presents the structure and automatic on-load voltage regulating principle of distributing transformer which employs solid state relay as non contact automatic on-load voltage regulat-ing tap changing switch .
The utility model discloses a protection system capable of realizing breaker failure triggering relevant trips of an interconnecting transform . The protection system analyzes the reasons that : if the circuit breaker on any one side is in failure , not all relevant trips of the circuit breakers on the power supply side are triggered , and the 220kV side breaker failure protection logic of the interconnecting transformer is changed , and the function of the breaker failure triggering relevant trips for interconnecting transformer protection is truly realized , and the technical regulation requirements is achieved , and guarantees on safe and stable operation of the power grid are supplied .
The IP camera adopts the technical scheme that a video collection device , a processor with a built-in video encoder and a built-in video decoder , a local display device and an FEC ( forward error correction ) interface circuit are comprised . The processor adopts i. MX27 ; the CSI ( Chinese system interface ) interface of the processor is connected with the video collection device ; an LCDC interface is connected with the local display device ; and the FEC interface is connected with the Ethernet through the FEC interface circuit and a network transformer in sequence . The IP camera istaken as a server ; client ( can be a computer device or a 3 G mobile phone ) is permitted to visit the camera through network ; the audio-frequency calling from the client is received by the camera ; and only by turning on the TV , voice communication and video communication with the client can be achieved .
This work builds upon two lines of research : it combines the modeling flexibility of prior work on content-based sparse attention with the efficiency gains from approaches based on local , temporal sparse attention . Our model , the Routing Transformer , endows self-attention with a sparse routing module based on online k-means while reducing the overall complexity of attention to $ O\left(n^{1.5}d\right)$ from $ O\left(n^2d\right)$ for sequence length $ n$ and hidden dimension $ d$. We show that our model outperforms comparable sparse attention models on language modeling on Wikitext-103 ( 15.8 vs 18.3 perplexity ) as well as on image generation on ImageNet-64 ( 3.43 vs 3.44 bits/dim ) while using fewer self-attention layers .
This paper describes the development of a compact n/8 inductive voltage divider ( IVD ) for the use in the frequency range between 1 and 100 kHz and voltages up to 5 V. The development includes a number of additional inductive components for the bootstrap calibration setup such as a supply transformer which ensures the galvanic isolation of the calibration setup , a calibration transformer , and a detection transformer . The desired frequency and uncertainty range requires a two-stage IVD design with coaxial windings , a triaxial differential branch , and voltage controlled shields to minimize capacitive stray currents .
This paper proposes a versatile convertible static transmission controller , in shunt-shunt mode , with dual active filters and photovoltaic ( PV ) power integration . The combined system aims to back up and control the power of a transmission transformer , as well as , improve the transmitted power quality to meet the grid standards and codes , especially the recently revised IEEE 1547 standards . The filters are also designed to eliminate the current and voltage harmonics due to the fluctuation in the injected PV power and the use of the switching power converters .
Usually the STN computes one affine transform for the whole image , considering a pedestrian ’s different parts have various orientations and sizes from each other , STN is not applicable to a part image . Inspired by STN , we design a Pose Transformer Network ( PTN ) which computes the affine transformation for each part in part image individually and combines 6 transformed parts together . Similar to STN , our PTN is also a small net and does n’t substantially increase the complexity of our training procedure .
document : Weighted Transformer Network for Machine Translation State - of - the - art results on neural machine translation often use attentional sequence - to - sequence models with some form of convolution or recursion .
Coreference resolution has been an active field of research in the past several decades and plays a vital role in many areas such as information extraction , document summarization , machine translation , and question answering systems . This paper presents a new coreference resolution approach by incorporating RoBERTa embedding with a neural multi-criteria decision making ( MCDM ) method . The proposed model does not use any syntactic and dependency parser .
Experimental results on these datasets show that the whole word masking could bring another significant gain . Moreover , we also examine the effectiveness of the Chinese pre-trained models : BERT , ERNIE , BERT-wwm , BERT-wwm-ext , RoBERTa-wwm-ext , and RoBERTa-wwm-ext-large . We release all the pre-trained models : \url{this https URL
Further approaches can be found in current literature . For instance , the Roberta Initiative ( raising girl ’s interest in technical topics ) conducted teacher training courses ( including certification ) only in robotics applying a train-the-trainer concept . ( Bredenfeld and Leimbach 2010 ) .
In our study , we used English BERT ( En-BERT ) , RoBERTa , DistilRoBERTa , and SVM based classifiers for the English language . For Hindi and Bangla language , multilingual BERT ( M-BERT ) , XLM-RoBERTa and SVM classifiers were used . Our best performing models are EN-BERT for English Subtask A ( Weighted F1 score of 0.73 , Rank 5/16 ) , SVM for English Subtask B ( Weighted F1 score of 0.87 , Rank 2/15 ) , SVM for Hindi Subtask A ( Weighted F1 score of 0.79 , Rank 2/10 ) , XLMRoBERTa for Hindi Subtask B ( Weighted F1 score of 0.87 , Rank 2/10 ) , SVM for Bangla Subtask A ( Weighted F1 score of 0.81 , Rank 2/10 ) , and SVM for Bangla Subtask B ( Weighted F1 score of 0.93 , Rank 4/8 ) .
Interpretation based Verification of Logic Programs Marco Comini , Roberta Gori , Giorgio Levi , Paolo Volpe Dipartimento di Informatica Università di Pisa Pisa , Italy
We further introduce new fine-tuning objectives to improve in-domain unsupervised fine-tuning to better utilize large amount of unlabeled in-domain data . We experiment on real world invoice and resume data sets and show that the proposed method outperforms strong text-based RoBERTa baselines by 6.3 % absolute F1 on invoices and 4.7 % absolute F1 on resumes . When evaluated in a few-shot setting , our method requires up to 30x less annotation data than the baseline to achieve the same level of performance at ~90 % F1 .
Methods We proposed a classifier for short text eligibility criteria based on ensemble learning , where a set of pretrained models was integrated . The pretrained models included state-of-the-art deep learning methods for training and classification , including Bidirectional Encoder Representations from Transformers ( BERT ) , XLNet , and A Robustly Optimized BERT Pretraining Approach ( RoBERTa ) . The classification results by the integrated models were combined as new features for training a Light Gradient Boosting Machine ( LightGBM ) model for eligibility criteria classification .
A Novel Transient Current Limiter Based on Three-Phase Thyristor Bridge for Y-yg Transformers A practical technique to measure transformer losses in high frequency SMPS On the Sizing and Benefits of Grounding Transformers with Distribution-Connected Inverters A three-phase unity-power-factor diode rectifier with active input current shaping Electromagnetic modeling of high voltage multi-level converter substations The Transformer Analogue Polynomial Equation Solver (TAPES) Performances Evaluation of On-Chip Large-Size-Tapped Transformer for MEMS Applications Traction transformation device and method Modeling and control of an LED-based airfield lighting system Real-time systems and methods for feeder automation distribution system for load balancing reconfigured Modelling of the 500 MW Back-to-Back Converter Station between Uruguay and Brazil in ATP Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation Longformer: The Long-Document Transformer Research on Access Mode of the Flexible DC Power Distribution System into AC System Study on stabling voltage equipment on rural low-voltage grid Protection system capable of realizing breaker failure triggering relevant trips of interconnecting transformer IP camera with two-way video communication function Efficient Content-Based Sparse Attention with Routing Transformers Two-Stage Coaxial Inductive Voltage Divider and Its Calibration Setup for Use Between 1 and 100 kHz Control and Real-Time Validation for Convertible Static Transmission Controller Enabled Dual Active Power Filters and PV Integration Pose-Driven Deep Convolutional Model for Person Re-identification Weighted Transformer Network for Machine Translation Coreference Resolution Using Neural MCDM and Fuzzy Weighting Technique Pre-Training with Whole Word Masking for Chinese BERT A Driving License for Intelligent Systems Aggression Identification in English, Hindi and Bangla Text using BERT, RoBERTa and SVM Abstract Interpretation Based Verification of Logic Programs Robust Layout-aware IE for Visually Rich Documents with Pre-trained Language Models An Ensemble Learning Strategy for Eligibility Criteria Text Classification for Clinical Trial Recruitment: Algorithm Development and Validation
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2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017 IEEE International Conference on Computer Vision (ICCV) ArXiv AAAI TRAC@LREC
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