111 citations · 277 across the 28 of their papers we have counts for
29 papers
Group Sequence Policy Optimization
Chujie Zheng, Shixuan Liu, Mingze Li +9
This paper introduces Group Sequence Policy Optimization (GSPO), our stable, efficient, and performant reinforcement learning algorithm for training large language models. Unlike p…
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Shenzhi Wang, Le Yu, Chang Gao +15
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a powerful approach to enhancing the reasoning capabilities of Large Language Models (LLMs), while its mechanis…
WorldPM: Scaling Human Preference Modeling
Binghai Wang, Runji Lin, Keming Lu +17
Motivated by scaling laws in language modeling that demonstrate how test loss scales as a power law with model and dataset sizes, we find that similar laws exist in preference mode…
Qwen3 Technical Report
An Yang, Anfeng Li, Baosong Yang +57
In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, a…
BARREL: Boundary-Aware Reasoning for Factual and Reliable LRMs
Junxiao Yang, Jinzhe Tu, Haoran Liu +9
Recent advances in Large Reasoning Models (LRMs) have shown impressive capabilities in mathematical and logical reasoning. However, current LRMs rarely admit ignorance or respond w…
Yi-Lightning Technical Report
Alan Wake, Bei Chen, C. X. Lv +41
This technical report presents Yi-Lightning, our latest flagship large language model (LLM). It achieves exceptional performance, ranking 6th overall on Chatbot Arena, with particu…
Aligning Instruction Tuning with Pre-training
Yiming Liang, Tianyu Zheng, Xinrun Du +12
Instruction tuning enhances large language models (LLMs) to follow human instructions across diverse tasks, relying on high-quality datasets to guide behavior. However, these datas…
The Lessons of Developing Process Reward Models in Mathematical Reasoning
Zhenru Zhang, Chujie Zheng, Yangzhen Wu +6
Process Reward Models (PRMs) emerge as a promising approach for process supervision in mathematical reasoning of Large Language Models (LLMs), which aim to identify and mitigate in…
ProcessBench: Identifying Process Errors in Mathematical Reasoning
Chujie Zheng, Zhenru Zhang, Beichen Zhang +6
As language models regularly make mistakes when solving math problems, automated identification of errors in the reasoning process becomes increasingly significant for their scalab…
From Theft to Bomb-Making: The Ripple Effect of Unlearning in Defending Against Jailbreak Attacks
Zhexin Zhang, Junxiao Yang, Yida Lu +5
Large Language Models (LLMs) are known to be vulnerable to jailbreak attacks. An important observation is that, while different types of jailbreak attacks can generate significantl…
Model Extrapolation Expedites Alignment
Chujie Zheng, Ziqi Wang, Heng Ji +2
Given the high computational cost of preference alignment training of large language models (LLMs), exploring efficient methods to reduce the training overhead remains an important…
On Prompt-Driven Safeguarding for Large Language Models
Chujie Zheng, Fan Yin, Hao Zhou +5
Prepending model inputs with safety prompts is a common practice for safeguarding large language models (LLMs) against queries with harmful intents. However, the underlying working…
Large Language Models Are Not Robust Multiple Choice Selectors
Chujie Zheng, Hao Zhou, Fandong Meng +2
Multiple choice questions (MCQs) serve as a common yet important task format in the evaluation of large language models (LLMs). This work shows that modern LLMs are vulnerable to o…
Click: Controllable Text Generation with Sequence Likelihood Contrastive Learning
Chujie Zheng, Pei Ke, Zheng Zhang +1
It has always been an important yet challenging problem to control language models to avoid generating texts with undesirable attributes, such as toxic language and unnatural repet…
CDConv: A Benchmark for Contradiction Detection in Chinese Conversations
Chujie Zheng, Jinfeng Zhou, Yinhe Zheng +6
Dialogue contradiction is a critical issue in open-domain dialogue systems. The contextualization nature of conversations makes dialogue contradiction detection rather challenging.…
CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
Jinfeng Zhou, Chujie Zheng, Bo Wang +2
Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy. However, existing empath…
EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with Large-Scale Pre-Training
Yuxian Gu, Jiaxin Wen, Hao Sun +8
Large-scale pre-training has shown remarkable performance in building open-domain dialogue systems. However, previous works mainly focus on showing and evaluating the conversationa…
AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation
Chujie Zheng, Sahand Sabour, Jiaxin Wen +2
Crowdsourced dialogue corpora are usually limited in scale and topic coverage due to the expensive cost of data curation. This would hinder the generalization of downstream dialogu…
COLD: A Benchmark for Chinese Offensive Language Detection
Jiawen Deng, Jingyan Zhou, Hao Sun +4
Offensive language detection is increasingly crucial for maintaining a civilized social media platform and deploying pre-trained language models. However, this task in Chinese is s…
On the Safety of Conversational Models: Taxonomy, Dataset, and Benchmark
Hao Sun, Guangxuan Xu, Jiawen Deng +6
Dialogue safety problems severely limit the real-world deployment of neural conversational models and have attracted great research interests recently. However, dialogue safety pro…
Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation
Chujie Zheng, Minlie Huang
Dialog models can be greatly strengthened through grounding on various external information, but grounded dialog corpora are usually not naturally accessible. In this work, we focu…
CEM: Commonsense-aware Empathetic Response Generation
Sahand Sabour, Chujie Zheng, Minlie Huang
A key trait of daily conversations between individuals is the ability to express empathy towards others, and exploring ways to implement empathy is a crucial step towards human-lik…
EVA: An Open-Domain Chinese Dialogue System with Large-Scale Generative Pre-Training
Hao Zhou, Pei Ke, Zheng Zhang +11
Although pre-trained language models have remarkably enhanced the generation ability of dialogue systems, open-domain Chinese dialogue systems are still limited by the dialogue dat…
PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Support
Hao Sun, Zhenru Lin, Chujie Zheng +2
Great research interests have been attracted to devise AI services that are able to provide mental health support. However, the lack of corpora is a main obstacle to this research,…