Papers by Xiaojiang Peng

2 papers
MPBench: A Comprehensive Multimodal Reasoning Benchmark for Process Errors Identification (2025.findings-acl)

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Challenge: Existing benchmarks of large language models focus on error detection, neglecting other scenarios like reasoning search.
Approach: et al. propose a multi-task, multimodal benchmark to assess effectiveness of PRMs . step correctness, answers aggregation and reasoning process search are evaluated . ethical principles of MPBench are based on a set of evaluation paradigms based in a text-based benchmark .
Outcome: a new benchmark assesses the effectiveness of large language models (LLMs) in multiple scenarios . it uses three evaluation paradigms to assess the effectiveness and compares them with existing models . a the proposed model improves reasoning accuracy by providing stepwise feedback for multi-step reasoning results .
A Challenge Dataset and Effective Models for Conversational Stance Detection (2024.lrec-main)

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Challenge: stance detection studies focus on evaluating stances within individual instances, hindering progress of conversational stance analysis.
Approach: They propose a multi-turn conversation stance detection dataset that encompasses multiple targets for conversational stance detector.
Outcome: The proposed dataset encompasses multiple targets for conversational stance detection.

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