activity
20242026
most citedOAG-Bench: A Human-Curated Benchmark for Academic Graph Mining

15 citations · 18 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CL2026

CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning

Dingling Xu, Ruobing Wang, Qingfei Zhao +8

Reasoning Language Models (RLMs) have significantly improved performance on complex tasks by extending the reasoning chain. However, these chains are prone to containing factual er…

cs.LG2026

Prefix-Guided On-Policy Distillation: Mining Golden Trajectories from Rollouts

Qingfei Zhao, Huan Song, Shuyu Tian +2

On-policy distillation (OPD) improves reasoning models by applying dense teacher supervision on student-sampled trajectories. However, scaling OPD to long-horizon reasoning exposes…

cs.LG2026

BPPO: Binary Prefix Policy Optimization for Efficient GRPO-Style Reasoning RL with Concise Responses

Qingfei Zhao, Huan Song, Shuyu Tian +2

Group Relative Policy Optimization (GRPO) is widely used for training reasoning models, but updating all sampled completions in each group incurs substantial cost and can reinforce…

cs.CL2026

Ruyi2.5 Technical Report

Huan Song, Shuyu Tian, Qingfei Zhao +5

We present Ruyi2.5, a multimodal familial model built on the AI Flow framework. Extending Ruyi2's "Train Once, Deploy Many" paradigm to the multimodal domain, Ruyi2.5 constructs a…

cs.LG2026

Theoretical Foundations of Scaling Law in Familial Models

Huan Song, Qingfei Zhao, Ting Long +4

Neural scaling laws have become foundational for optimizing large language model (LLM) training, yet they typically assume a single dense model output. This limitation effectively…

cs.CL2025

R-Search: Empowering LLM Reasoning with Search via Multi-Reward Reinforcement Learning

Qingfei Zhao, Ruobing Wang, Dingling Xu +2

Large language models (LLMs) have notably progressed in multi-step and long-chain reasoning. However, extending their reasoning capabilities to encompass deep interactions with sea…

cs.CL2024★ 1 cited

PrefRAG: Preference-Driven Multi-Source Retrieval Augmented Generation

Qingfei Zhao, Ruobing Wang, Yukuo Cen +3

Retrieval-Augmented Generation (RAG) has emerged as a reliable external knowledge augmentation technique to mitigate hallucination issues and parameterized knowledge limitations in…

cs.CL2024★ 2 cited

LongRAG: A Dual-Perspective Retrieval-Augmented Generation Paradigm for Long-Context Question Answering

Qingfei Zhao, Ruobing Wang, Yukuo Cen +4

Long-Context Question Answering (LCQA), a challenging task, aims to reason over long-context documents to yield accurate answers to questions. Existing long-context Large Language…

cs.CL2024

DeepNote: Note-Centric Deep Retrieval-Augmented Generation

Ruobing Wang, Qingfei Zhao, Yukun Yan +9

Retrieval-Augmented Generation (RAG) mitigates factual errors and hallucinations in Large Language Models (LLMs) for question-answering (QA) by incorporating external knowledge. Ho…

cs.DL2024★ 15 cited

OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining

Fanjin Zhang, Shijie Shi, Yifan Zhu +19

With the rapid proliferation of scientific literature, versatile academic knowledge services increasingly rely on comprehensive academic graph mining. Despite the availability of p…