Papers by Haosen Wang
Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models (2026.findings-acl)
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Can Xu, Lingyong Yan, Jiayi Wu, Haosen Wang, Shuaiqiang Wang, Yuchen Li, Jizhou Huang, Dawei Yin, Xiang Li
| Challenge: | Existing training paradigms rely on outcome-oriented rewards, which provide insufficient signal for shaping the complex, multi-step reasoning process. |
| Approach: | They propose a framework that integrates large reasoning models with retrieval-augmented generation to improve reasoning fidelity and verification rigor. |
| Outcome: | Experiments on multiple benchmarks demonstrate the effectiveness of the proposed framework. |
ProgressLM: Towards Progress Reasoning in Vision-Language Models (2026.acl-long)
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| Challenge: | Existing models for task progress estimation lack long-horizon and dynamic reasoning . estimating how much of a task has been completed requires long-term reasoning based on partial information. |
| Approach: | They propose a benchmark for evaluating progress reasoning from a single observation . they instantiate a two-stage paradigm that combines episodic retrieval with mental simulation . |
| Outcome: | The proposed benchmark improves on 14 VLMs on a small scale and shows common failure patterns. |
Flow-Based Page Unique Semantic Mapping Architecture for Document Visual Question Answering (2026.acl-long)
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| Challenge: | Document Visual Question Answering (DocVQA) aims to generate answers by understanding textual, layout, and visual elements within document images. |
| Approach: | They propose a Flow-Based Page Unique Semantic Mapping Architecture to solve the distinguishability problem among semantically similar pages. |
| Outcome: | The proposed model outperforms existing methods in evidence localization and answer generation. |