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20242026
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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.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…

cs.CL2025

SafeLawBench: Towards Safe Alignment of Large Language Models

Chuxue Cao, Han Zhu, Jiaming Ji +7

With the growing prevalence of large language models (LLMs), the safety of LLMs has raised significant concerns. However, there is still a lack of definitive standards for evaluati…

cs.CL2024

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models

Lionel Z. Wang, Ka Chung Ng, Yiming Ma +1

Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language models (LLMs), as part of generative AI,…