collaborators

10 papers

cs.AI2026

Herculean: An Agentic Benchmark for Financial Intelligence

Xueqing Peng, Zhuohan Xie, Yupeng Cao +60

As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carry out financial professional…

cs.CV2026

Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward

Shizhan Gong, Minda Hu, Qiyuan Zhang +2

Vision-language models (VLMs) have achieved remarkable success across diverse tasks. However, concerns about their trustworthiness persist, particularly regarding tendencies to lea…

cs.IR2026

Give Users the Wheel: Towards Promptable Recommendation Paradigm

Fuyuan Lyu, Chenglin Luo, Qiyuan Zhang +6

Conventional sequential recommendation models have achieved remarkable success in mining implicit behavioral patterns. However, these architectures remain structurally blind to exp…

cs.AI2026

RubricBench: Aligning Model-Generated Rubrics with Human Standards

Qiyuan Zhang, Junyi Zhou, Yufei Wang +8

As Large Language Model (LLM) alignment evolves from simple completions to complex, highly sophisticated generation, Reward Models are increasingly shifting toward rubric-guided ev…

cs.AI2026

Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models

Qiyuan Zhang, Yufei Wang, Tianhe Wu +5

Recent advancements in Generative Reward Models (GRMs) have demonstrated that scaling the length of Chain-of-Thought (CoT) reasoning considerably enhances the reliability of evalua…

cs.CL2026

From Verifiable Dot to Reward Chain: Harnessing Verifiable Reference-based Rewards for Reinforcement Learning of Open-ended Generation

Yuxin Jiang, Yufei Wang, Qiyuan Zhang +6

Reinforcement learning with verifiable rewards (RLVR) succeeds in reasoning tasks (e.g., math and code) by checking the final verifiable answer (i.e., a verifiable dot signal). How…