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20242026
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cs.CL2026

Qwen-AgentWorld: Language World Models for General Agents

Yuxin Zuo, Zikai Xiao, Li Sheng +30

A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigat…

cs.CL2026

Deeper is Not Always Better: Mitigating the Alignment Tax via Confident Layer Decoding

Xuanming Zhang, Sining Zhoubian, Yuxuan Chen +8

Autoregressive generation in large language models (LLMs) conventionally decodes from the final layer, assuming that deeper representations yield more reliable next-token predictio…

cs.CL2025

Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free

Zihan Qiu, Zekun Wang, Bo Zheng +10

Gating mechanisms have been widely utilized, from early models like LSTMs and Highway Networks to recent state space models, linear attention, and also softmax attention. Yet, exis…

cs.CL2024

A Survey on Self-Evolution of Large Language Models

Zhengwei Tao, Ting-En Lin, Xiancai Chen +7

Large language models (LLMs) have significantly advanced in various fields and intelligent agent applications. However, current LLMs that learn from human or external model supervi…

cs.CL2024

AI Hospital: Benchmarking Large Language Models in a Multi-agent Medical Interaction Simulator

Zhihao Fan, Jialong Tang, Wei Chen +5

Artificial intelligence has significantly advanced healthcare, particularly through large language models (LLMs) that excel in medical question answering benchmarks. However, their…