6 papers
SKILLER: Language-Level Reinforcement Learning for Reusable Skill Extraction in Small Language Models
Chenhao Dang, Siyuan Xiong, Conghui He +1
Agent skills represent a standardized format for packaging procedural knowledge and domain expertise, serving within agent harness systems as an essential mechanism to continually…
PosterMELD: Multi-Agent Paper-to-Poster Generation for Controllable Design Diversity with Editable Print-Ready Outputs
Haojie Hu, Chenhao Dang, Yaojia Liu +3
Scientific poster construction compresses a long multimodal paper into a readable, editable canvas. Existing systems hide request-level failures by scoring only completed outputs;…
Holistic Data Scheduler for LLM Pre-training via Multi-Objective Reinforcement Learning
Chenhao Dang, Jing Ma, Mingjie Liao
The composition of training data, governed by the diversity of sources and their mixing strategy, is a cornerstone of Large Language Model (LLM) pre-training. Online Data Mixing (O…
ReMMD: Realistic Multilingual Multi-Image Agentic Verification for Multimodal Misinformation Detection
Chenhao Dang, Dantong Zhu, Jun Yang +2
Multimodal misinformation detection is increasingly important because viral posts now combine long multilingual narratives, several images, mixed provenance, and subtle cross-modal…
AC-ODM: Actor--Critic Online Data Mixing for Sample-Efficient LLM Pretraining
Jing Ma, Chenhao Dang, Mingjie Liao
Optimizing pretraining data composition is pivotal for LLM generalization. While dynamic mixing outperforms static strategies by capturing evolving training dynamics, current metho…
Breaking the Adversarial Robustness-Performance Trade-off in Text Classification via Manifold Purification
Chenhao Dang, Jing Ma
A persistent challenge in text classification (TC) is that enhancing model robustness against adversarial attacks typically degrades performance on clean data. We argue that this c…