3 papers
cs.AI2026
HIPIF: Hierarchical Planning and Information Folding for Long-Horizon LLM Agent Learning
Juncheng Diao, Zhicong Lu, Peiguang Li +6
While Large Language Models (LLMs) have demonstrated strong capabilities as autonomous agents across a wide range of tasks, their performance often degrades in multi-turn long-hori…
cs.CV2026
Do All Vision Transformers Need Registers? A Cross-Architectural Reassessment
Spiros Baxevanakis, Platon Karageorgis, Ioannis Dravilas +1
Training Vision Transformers (ViTs) presents significant challenges, one of which is the emergence of artifacts in attention maps, hindering their interpretability. Darcet et al. (…
cs.LG2026
From Atoms to Chains: Divergence-Guided Reasoning Curriculum for Unlabeled LLM Domain Adaptation
Yongqi Wang, Xiaofeng Ji, Jie Wang +6
Adapting Large Language Models (LLMs) to specialized domains without human-annotated data is a crucial yet formidable challenge. Widely adopted knowledge distillation methods often…