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From the 1 of 9 linked papers with an AI index.

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20242026
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cs.CL2026

CAST: Game Solvers as Turn-Level Teachers for LLM Agents

Yu Wang, Yi-Kai Zhang, Wentao Shi +8

Training large language models (LLMs) to act in long-horizon games is a promising step toward generalist decision-making, yet reinforcement learning with verifiable rewards (RLVR)…

cs.CL2026

When2Speak: A Dataset for Temporal Participation and Turn-Taking in Multi-Party Conversations for Large Language Models

Vihaan Nama, Shreya Mendi, Zian Ye +1

Large Language Models (LLMs) excel at generating contextually appropriate responses but remain poorly calibrated for multi-party conversations, where deciding when to speak is as c…

cs.CL2026

Learning to Self-Verify Makes Language Models Better Reasoners

Yuxin Chen, Yu Wang, Yi Zhang +9

Recent large language models (LLMs) achieve strong performance in generating promising reasoning paths for complex tasks. However, despite powerful generation ability, LLMs remain…

cs.CL2025

VisualTrap: A Stealthy Backdoor Attack on GUI Agents via Visual Grounding Manipulation

Ziang Ye, Yang Zhang, Wentao Shi +3

Graphical User Interface (GUI) agents powered by Large Vision-Language Models (LVLMs) have emerged as a revolutionary approach to automating human-machine interactions, capable of…

cs.CL2024

Disentangling Reasoning Tokens and Boilerplate Tokens For Language Model Fine-tuning

Ziang Ye, Zhenru Zhang, Yang Zhang +3

When using agent-task datasets to enhance agent capabilities for Large Language Models (LLMs), current methodologies often treat all tokens within a sample equally. However, we arg…