4 papers
Agentic Context Learning with Self-Discovered Specification
Jike Zhong, Ming Li, Yuxiang Lai +8
Context learning is an emerging inference-time task where LLMs must learn and apply novel, task-specific knowledge from intricate contexts absent from pre-training; even frontier m…
Reroute, Don't Remove: Recoverable Visual Token Routing for Vision-Language Models
Cheng-Yu Yang, Shao-Yuan Lo, Yu-Lun Liu
Vision-language models (VLMs) project images into hundreds to thousands of visual tokens, making decoder inference expensive in both attention computation and KV-cache memory. Exis…
From Shortcuts to Reasoning: Robust Post-Training of Theory of Mind with Reinforcement Learning
Jike Zhong, Yuxiang Lai, Ming Li +5
Theory of Mind (ToM) is a must-acquire skill for modern foundation model systems to operate effectively and safely in the real world. Recent works have explored honing ToM via post…
ALICE: A Multifaceted Evaluation Framework of Large Audio-Language Models' In-Context Learning Ability
Yen-Ting Piao, Jay Chiehen Liao, Wei-Tang Chien +5
While Large Audio-Language Models (LALMs) have been shown to exhibit degraded instruction-following capabilities, their ability to infer task patterns from in-context examples unde…