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From the 1 of 40 linked papers with an AI index.

most citedReimagining Legal Fact Verification with GenAI: Toward Effective Human-AI Collaboration

2 citations · 2 across the 23 of their papers we have counts for

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cs.CL2026

IndexMem: Learned KV-Cache Eviction with Latent Memory for Long-Context LLM Inference

Xintong Yang, Hao Gu, Binxing Xu +6

Large Language Models (LLMs) are increasingly expected to operate over long contexts, yet standard softmax attention incurs a KV cache that grows linearly with sequence length, qui…

cs.CL2026

Self-Evolving Deep Research via Joint Generation and Evaluation

Han Zhu, Chengkun Cai, Yuanfeng Song +3

Large Language Models (LLMs) have become increasingly adopted in daily applications, with deep research standing out as a particularly important capability. Unlike traditional ques…

cs.CL2026

Not Just the Destination, But the Journey: Reasoning Traces Causally Shape Generalization Behaviors

Pengcheng Wen, Yanxu Zhu, Jiapeng Sun +5

Chain-of-Thought (CoT) is often viewed as a window into LLM decision-making, yet recent work suggests it may function merely as post-hoc rationalization. This raises a critical ali…

cs.CL2026

ThinkPatterns-21k: A Systematic Study on the Impact of Thinking Patterns in LLMs

Pengcheng Wen, Jiaming Ji, Chi-Min Chan +5

Large language models (LLMs) have demonstrated enhanced performance through the \textit{Thinking then Responding} paradigm, where models generate internal thoughts before final res…

cs.CL2026

AMSafety: Towards Data Efficient Alignment of Multi-modal Multi-turn Safety for MLLMs

Han Zhu, Jiale Chen, Chengkun Cai +8

Multi-modal Large Language Models (MLLMs) are increasingly deployed in interactive applications. However, their safety vulnerabilities become pronounced in multi-turn multi-modal s…

cs.CL2025

SafeMT: Multi-turn Safety for Multimodal Language Models

Han Zhu, Juntao Dai, Jiaming Ji +8

With the widespread use of multi-modal Large Language models (MLLMs), safety issues have become a growing concern. Multi-turn dialogues, which are more common in everyday interacti…