Papers by Hefei Ling

2 papers
EntroBench: Evaluating LLM Watermarking Under Multi-Entropy Scenarios and Practical User Operations (2026.findings-acl)

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Challenge: Existing evaluations of large language models (LLMs) watermarking are limited to fixed entropy settings.
Approach: They propose a benchmark for LLM watermarking that systematically covers three entropy levels and seven representative tasks.
Outcome: The proposed framework covers three entropy levels and seven representative tasks.
Beyond Query Bias: Candidate-Aware Iterative Refinement for Zero-Shot Composed Image Retrieval (2026.findings-acl)

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Challenge: Existing methods to retrieve target images suffer from inherent cognitive bias due to unknown candidate distribution.
Approach: They propose a training-free framework that reframes ZS-CIR as a self-correcting process . they propose to use retrieved results as feedback to perceive the candidate distribution .
Outcome: Experiments on public benchmarks show that CoRR outperforms other SOTA methods.

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