7 papers
RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains
Haoxiang Jiang, Zihan Dong, Tianci Liu +5
Pointwise reward modeling offers critical signals for LLM post-training, yet struggles with absolute scoring in subjective, non-verifiable settings. Rubric-based methods address th…
Knowledge Graph Augmented Large Language Models for Disease Prediction
Ruiyu Wang, Tuan Vinh, Ran Xu +5
Electronic health records (EHRs) enable strong clinical prediction, but explanations are often coarse and hard to use for patient-level decisions. We propose a knowledge graph (KG)…
Incentivizing Agentic Reasoning in LLM Judges via Tool-Integrated Reinforcement Learning
Ran Xu, Jingjing Chen, Jiayu Ye +4
Large Language Models (LLMs) are widely used as judges to evaluate response quality, providing a scalable alternative to human evaluation. However, most LLM judges operate solely o…
Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training
Ran Xu, Tianci Liu, Zihan Dong +6
Standard reward models typically predict scalar scores that fail to capture the multifaceted nature of response quality in non-verifiable domains, such as creative writing or open-…
OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM Alignment
Tianci Liu, Ran Xu, Tony Yu +4
Reward modeling lies at the core of reinforcement learning from human feedback (RLHF), yet most existing reward models rely on scalar or pairwise judgments that fail to capture the…
HypKG: Hypergraph-based Knowledge Graph Contextualization for Precision Healthcare
Yuzhang Xie, Xu Han, Ran Xu +3
Knowledge graphs (KGs) are important products of the semantic web, which are widely used in various application domains. Healthcare is one of such domains where KGs are intensively…