Papers by Honggang Zhang
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? (2025.acl-long)
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Runqi Qiao, Qiuna Tan, Guanting Dong, MinhuiWu MinhuiWu, Chong Sun, Xiaoshuai Song, Jiapeng Wang, Zhuoma GongQue, Shanglin Lei, YiFan Zhang, Zhe Wei, Miaoxuan Zhang, Runfeng Qiao, Xiao Zong, Yida Xu, Peiqing Yang, Zhimin Bao, Muxi Diao, Chen Li, Honggang Zhang
| Challenge: | Existing benchmarks focus more on end-to-end performance, but neglect the underlying principles of knowledge acquisition and generalization. |
| Approach: | They propose a benchmark specifically designed to explore the problem-solving principles by decomposing 6.5K visual math problems into 10.9K step-level questions for evaluation. |
| Outcome: | The proposed benchmark covers 6.5K visual math problems and 10.9K step-level questions spanning 5 layers of knowledge granularity and 67 hierarchical knowledge concepts. |
Beyond Compromise: Pareto-Lenient Consensus for Efficient Multi-Preference LLM Alignment (2026.findings-acl)
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| Challenge: | Recent approaches to align LLMs with diverse human values are based on static linear scalarization or rigid gradient projection . however, these approaches often sacrifice potential global Pareto improvements to avoid transient local trade-offs. |
| Approach: | They propose a game-theoretic framework that reimagines alignment as a dynamic negotiation process. |
| Outcome: | The proposed framework breaks the deadlock between static linear scalarization and rigid gradient projection . it allows the model to escape local degradation and explore the distal Pareto-optimal frontier . |
V-Oracle: Making Progressive Reasoning in Deciphering Oracle Bones for You and Me (2025.acl-long)
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Runqi Qiao, Qiuna Tan, Guanting Dong, MinhuiWu MinhuiWu, Jiapeng Wang, YiFan Zhang, Zhuoma GongQue, Chong Sun, Yida Xu, Yadong Xue, Ye Tian, Zhimin Bao, Lan Yang, Chen Li, Honggang Zhang
| Challenge: | Deciphering oracle bone scripts using AI technology is not an overnight task due to the evolution of written language over millennia. |
| Approach: | They propose a framework that utilizes Large Multi-modal Models (LMMs) for interpreting Oracle Bone Script (OBS). |
| Outcome: | The proposed framework provides quantitative analyses and superior deciphering capability. |
Amadeus: Autoregressive Model with Bidirectional Attribute Modelling for Symbolic Music (2026.acl-long)
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| Challenge: | Existing symbolic music generation models represent musical notes as a sequence of attribute tokens with fixed unidirectional dependencies. |
| Approach: | They propose a symbolic music generation framework that adopts a autoregressive and a discrete diffusion architectures for note attributes. |
| Outcome: | The proposed framework improves state-of-the-art models across objective and subjective metrics. |