Papers by Linghao Zhang

2 papers
DI-BENCH: Benchmarking Large Language Models on Dependency Inference with Testable Repositories at Scale (2025.findings-acl)

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Challenge: Existing studies highlight that dependency-related issues cause over 40% of observed runtime errors on the generated repository.
Approach: They propose a large-scale benchmark and evaluation framework specifically designed to assess LLMs’ capability on dependency inference.
Outcome: The proposed model achieves only a 48% execution pass rate on Python, indicating room for improvement.
Theorem-Validated Reverse Chain-of-Thought Problem Generation for Geometric Reasoning (2025.emnlp-main)

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Challenge: Existing methods for generating geometric reasoning data through Chain-of-Thought (CoT) frameworks face three fundamental limitations: 1) lack of high-quality annotations and domain-specific expertise to ensure theorem-grounded diagrams. 2) lack of a coherent model; 3) lack of coherent model.
Approach: They propose a two-stage Theorem-Validated Reverse Chain-of-Thought Reasoning Synthesis framework that synthesizes theorematic diagrams with structured descriptions and properties.
Outcome: The proposed framework expands theorem-type coverage, corrects misunderstandings, and enhances geometric reasoning.

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