Papers by Chunhua Liao

2 papers
REALM: Recursive Relevance Modeling for LLM-based Document Re-Ranking (2025.emnlp-main)

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Challenge: Existing LLMs face ranking uncertainty, unstable top-k recovery, and high token cost due to token-intensive prompting.
Approach: They propose a re-ranking framework that captures uncertainty and refines LLM-derived relevance through recursive Bayesian updates.
Outcome: The proposed framework outperforms state-of-the-art re-rankers while reducing token usage and latency.
Beyond Code Pairs: Dialogue-Based Data Generation for LLM Code Translation (2026.acl-long)

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Challenge: Large language models (LLMs) have shown remarkable capabilities in code translation, yet their performance deteriorates in low-resource programming domains such as Fortran and emerging frameworks like CUDA .
Approach: They propose a dual-LLM Questioner–Solver pipeline that integrates external knowledge from compilers and runtime feedback to generate verified translations and multi-turn dialogues.
Outcome: The proposed model outperforms proprietary models on key metrics like compilation success and accuracy.

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