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From the 1 of 11 linked papers with an AI index.

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cs.CL2026

Erase-then-Delta Attention: Decoupling Erase and Write Addresses in Delta-Rule Linear Attention

Xiao Li, Chengruidong Zhang, Hao Luo +15

Delta-rule linear attention improves recurrent memory updates by correcting what is already stored at the current write address before writing new content. However, the active corr…

cs.CL2026

Tool Calling is Linearly Readable and Steerable in Language Models

Zekun Wu, Ze Wang, Seonglae Cho +4

When a tool-calling agent picks the wrong tool, the failure is invisible until execution: the email gets sent, the meeting gets missed. As agents take on consequential actions, one…

cs.CL2026

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context

Zekun Wang, Anant Gupta, Zihan Dong +1

Large language models (LLMs) increasingly receive information as streams of passages, conversations, and long-context workflows. While longer context windows expose more evidence,…

cs.CL2026

A Unified View of Attention and Residual Sinks: Outlier-Driven Rescaling is Essential for Transformer Training

Zihan Qiu, Zeyu Huang, Kaiyue Wen +16

We investigate the functional role of emergent outliers in large language models, specifically attention sinks (a few tokens that consistently receive large attention logits) and r…

cs.CL2025

VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos

Dunjie Lu, Yiheng Xu, Junli Wang +12

Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgen…