Update README.md

README.md

@@ -13,10 +13,16 @@ tags:
 
 configs:      
   - config_name: core
-    description: Randomized updates (keys shuffled across key–value pairs). Recommended as the primary/SOTA comparison setting. At the highest stress tier, all tested models (as of Ma  2025) fail to reliably recover the final value.
+    description: Randomized updates (keys shuffled across key–value pairs). Recommended as the primary/SOTA comparison setting. At the highest stress tier, all tested models (as of May 2025) fail to reliably recover the final value.
     data_files:
       - split: test
         path: core.parquet
+  
+  - config_name: sequential_additional
+    description: Non-randomized – clear and strict sequential blocks; prove short context(token=5k-8k) can already have a strong context interference for most LLMs. Even with this well formatted data, many model's the performance still drop rapidly.
+    data_files:
+      - split: test
+        path: sequential_additional.parquet
 
     
 
@@ -147,7 +153,7 @@ What is the current value (the last value) for key1 key2....key46?
 
 
 **Result**  
-- In this mode, **most Modern LLMs still confuse the last value with earlier value after only 50–100 updates** (fewer than 12–25k tokens, far less than any LLMs' context window).  
+- In this mode, **most Modern LLMs (all <600B) still confuse the last value with earlier value after only 50–100 updates** (fewer than 12–25k tokens, far less than any LLMs' context window).  
 - Models quickly confuse earlier values with the most recent one.  
 - This is the **original and most simple test**
 - Performance for this mode is also **reported in our paper (Figure 4).**
@@ -159,8 +165,8 @@ What is the current value (the last value) for key1 key2....key46?
 This repository hosts the **PI-LLM** dataset.  
 Currently it includes two files:
 
-- **core.parquet** → the main dataset  
-- **additional_sequential.parquet** →  esasy/sequntial mode, still hard for many LLMs but super easy for humans, with just ordered update blocks.
+- **core.parquet** → Main dataset (randomized updates). Recommended as the primary/SOTA comparison setting; All tested models fail to reliably retrieve the last value. 
+- **sequential_additional.parquet** →  Sequential mode (non-randomized, strict per-key ordered update blocks). Trivial for humans yet still challenging for many LLMs; smaller (all <600B) models are especially affected, with proactive-interference effects clearly exposed (even in short contexts, ~5–8k tokens).
 
 
 ## Quick Start - Evaluate Your Model