papers

Publications (32)

cs.CL2026

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

Haoran Luo, Haihong E, Guanting Chen +8

Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that lacks structural semantics. Graph…

cs.CL2026

HiFlow: Hierarchical Feedback-Driven Optimization for Constrained Long-Form Text Generation

Yifan Zhu, Guanting Chen, Bing Wei +1

Large language models perform well in short text generation but still struggle with long text generation, particularly under complex constraints. Such tasks involve multiple tightl…

cs.LG2024

Reward Modeling with Ordinal Feedback: Wisdom of the Crowd

Shang Liu, Yu Pan, Guanting Chen +1

Learning a reward model (RM) from human preferences has been an important component in aligning large language models (LLMs). The canonical setup of learning RMs from pairwise pref…

cs.CL2025

DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

DeepSeek-AI, Aixin Liu, Aoxue Mei +260

We introduce DeepSeek-V3.2, a model that harmonizes high computational efficiency with superior reasoning and agent performance. The key technical breakthroughs of DeepSeek-V3.2 ar…

cs.LG2024

Towards Better Understanding of In-Context Learning Ability from In-Context Uncertainty Quantification

Shang Liu, Zhongze Cai, Guanting Chen +1

Predicting simple function classes has been widely used as a testbed for developing theory and understanding of the trained Transformer's in-context learning (ICL) ability. In this…

stat.ML2024

Learning to Make Adherence-Aware Advice

Guanting Chen, Xiaocheng Li, Chunlin Sun +1

As artificial intelligence (AI) systems play an increasingly prominent role in human decision-making, challenges surface in the realm of human-AI interactions. One challenge arises…