Papers by Zixu Li

2 papers
Reason-Code: Reliable Code Generation via Test-Driven Monte Carlo Tree Search (2026.acl-industry)

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Challenge: Large Language Models (LLMs) are widely used for code generation, but their performance degrades on complex tasks.
Approach: They propose an inference-time framework that formulates code generation as a search process guided by execution feedback.
Outcome: The proposed framework improves reliability without paying full cost of additional sampling under strict latency budgets.
TEMA: Anchor the Image, Follow the Text for Multi-Modification Composed Image Retrieval (2026.acl-long)

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Challenge: Composed Image Retrieval (CIR) is an image retrieval paradigm that enables users to retrieve a target image using a multimodal query that consists of a reference image and modification text.
Approach: They propose a text-oriented entity mapping architecture that allows users to use a reference image and modification text to retrieve a target image.
Outcome: The proposed framework is superior in both original and multi-modification scenarios while maintaining an optimal balance between retrieval accuracy and computational efficiency.

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