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cs.CL2026

DAIS: Dependency-Aware Intermediate QA Supervision for Complex Reasoning

Yu Wang, Ming Fan, Xicheng Zhang +5

Chain-of-thought (CoT) supervision exposes intermediate rationales, but flat rationale targets usually optimize a single reasoning sequence and provide limited supervision on how l…

cs.CL2026

ReviewGrounder: Improving Review Substantiveness with Rubric-Guided, Tool-Integrated Agents

Zhuofeng Li, Yi Lu, Dongfu Jiang +7

The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-based reviewers often generate s…

cs.CL2026

CocoaBench: Evaluating Unified Digital Agents in the Wild

CocoaBench Team, Shibo Hao, Zhining Zhang +29

LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds and models are increasingly int…

cs.CL2026

RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game

Shijia Xu, Yu Wang, Xiaolong Jia +3

Despite the widespread adoption of Large Language Models (LLMs) in Legal AI, their utility for automated contract revision remains impeded by hallucinated safety and a lack of rigo…

cs.CL2026

Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS

Shijia Xu, Zhou Wu, Xiaolong Jia +3

Retrieval-augmented generation (RAG) substantially extends the knowledge boundary of large language models. However, it still faces two major challenges when handling complex reaso…

cs.CL2026

DLLM Agent: See Farther, Run Faster

Huiling Zhen, Weizhe Lin, Renxi Liu +15

Diffusion large language models (DLLMs) have emerged as an alternative to autoregressive (AR) decoding with appealing efficiency and modeling properties, yet their implications for…