Papers by Hefei Chen

2 papers
SOP-Maze: Evaluating Large Language Models on Complicated Business Standard Operating Procedures (2026.findings-acl)

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Challenge: Large language models (LLMs) are widely deployed as domain-specific agents, but evaluation of their capabilities in such contexts has not been fully explored.
Approach: They propose a benchmark to evaluate LLMs' ability to follow instructions and make decisions in real-world scenarios.
Outcome: The proposed benchmark is constructed from real-world business data and adapted into 23 complex SOP scenarios.
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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