7 papers
Reward as An Agent for Embodied World Models
Pu Li, Zhigang Lin, Qiang Wu +3
While RL has become a promising tool for refining world models, existing methods largely rely on conservative rollouts near the training distribution, limiting exploration, behavio…
Repeated post-training is not Self-improving: Diagnosing Scientific Amnesia in Continual DPO Pipelines
Jianzhe Lin, Fei Wang, Xiaolin Li +2
Industrial LLM teams often ship behavior updates by repeatedly DPO-training a base model on sequences of related preference-data campaigns. The dominant failure mode in this regime…
Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs
Weiwei Ding, Zixuan Li, Long Bai +7
Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations. Existing LLM-KG integration frame…
Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
Yiyang Lu, Woong Shin, Ahmad Maroof Karimi +3
Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely on pixel interpretation, cr…
Towards Knowledgeable Deep Research: Framework and Benchmark
Wenxuan Liu, Zixuan Li, Long Bai +13
Deep Research (DR) requires LLM agents to autonomously perform multi-step information seeking, processing, and reasoning to generate comprehensive reports. In contrast to existing…
KnowCoder-A1: Incentivizing Agentic Reasoning Capability with Outcome Supervision for KBQA
Zhuo Chen, Fei Wang, Zixuan Li +6
Knowledge Base Question Answering (KBQA) aims to answer natural-language questions over a structured Knowledge Base (KB). Recent work improves KBQA by adopting an agentic reasoning…