Harder Is Better: Boosting Mathematical Reasoning via Difficulty-Aware GRPO and Multi-Aspect Question Reformulation
Yanqi Dai · Yuxiang Ji · Xiao Zhang · Yong Wang · Xiangxiang Chu · Zhiwu Lu
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Yanqi Dai · Yuxiang Ji · Xiao Zhang · Yong Wang · Xiangxiang Chu · Zhiwu Lu
Yifei Wang · Yueqi Wang · Zhenrui Yue · Huimin Zeng · Yong Wang · Ismini Lourentzou · Zhengzhong Tu · Xiangxiang Chu · Julian McAuley
Xiangxiang Chu · Hailang Huang · Xiao Zhang · Fei Wei · Yong Wang
Zengbin Wang · Xuecai Hu · Yong Wang · Feng Xiong · Man Zhang · Xiangxiang Chu
Yuxiang Ji · Ziyu Ma · Yong Wang · Guanhua Chen · Xiangxiang Chu · Liaoni Wu
Peng Lai · Zhihao Ou · Yong Wang · Longyue Wang · Jian Yang · Yun Chen · Guanhua Chen
Zengbin Wang · Feng Xiong · Liang Lin · Xuecai Hu · Yong Wang · Yanlin Wang · Man Zhang · Xiangxiang Chu
Reinforcement learning with verifiable rewards (RLVR) has significantly advanced the reasoning ability of vision-language models (VLMs). However, the inherent text-dominated nature of VLMs often leads to insufficient visual faithfulness, characterized by sparse attention activation to visual toke...
Zeguan Xiao · Siqing Li · Yong Wang · Xuetao Wei · Jian Yang · Yun Chen · Guanhua Chen
Machine unlearning for large language models (LLMs) aims to remove targeted knowledge while preserving general capability. In this paper, we recast LLM unlearning as an asymmetric two-task problem: retention is the primary objective and forgetting is an auxiliary. From this perspective, we propos...
Shun Zou · Yong Wang · Zehui Chen · Lin Chen · Chongyang Tao · Feng Zhao · Xiangxiang Chu
Diffusion Large Language Models (dLLMs) have recently become a promising alternative to autoregressive large language models (ARMs). Semi-autoregressive (Semi-AR) decoding is widely employed in base dLLMs and advanced decoding strategies due to its superior performance. However, our observations...
Shidong Yang · Ziyu Ma · Tongwen Huang · Yiming Hu · Yong Wang · Xiangxiang Chu
Reinforcement learning for LLM agents is typically conducted on a static data distribution, which fails to adapt to the agent’s evolving behavior and leads to poor coverage of complex environment interactions. To address these challenges, we propose CoEvolve, an agent-data mutual evolution framew...
Yuxiang Ji · Yong Wang · Ziyu Ma · Yiming Hu · Hailang Huang · Xuecai Hu · Guanhua Chen · Liaoni Wu · Xiangxiang Chu
The image geolocalization task aims to predict the location where an image was taken anywhere on Earth using visual clues.Existing large vision-language model (LVLM) approaches leverage world knowledge, chain-of-thought reasoning, and agentic capabilities, but overlook a common strategy used by h...
Yanlin Wang · Ziyao Zhang · Chong Wang · Xinyi Xu · Mingwei Liu · Yong Wang · Jiachi Chen · Zibin Zheng
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, but their proficiency in producing secure code remains a critical, under-explored area. Existing benchmarks often fall short by relying on synthetic vulnerabilities or evaluating functional correctness in i...
Jing Zhang · Lianghong Guo · Yanlin Wang · Terry Yue Zhuo · Yong Wang · Mingwei Liu · Jiachi Chen · Ensheng Shi · Yuchi Ma · Hongyu Zhang · Zibin Zheng
The Development Knowledge Question Answering (Dev Knowledge QA) task aims to provide accurate natural language answers to knowledge-seeking questions during software development. To investigate the importance of Dev Knowledge QA in AI-assisted software development and the extent to which it has b...