Papers by Zhaoling Chen

2 papers
LocAgent: Graph-Guided LLM Agents for Code Localization (2025.acl-long)

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Challenge: Existing approaches struggle to efficiently navigate complex codebases when identifying relevant code snippets.
Approach: They propose a graph-guided agent framework that addresses code localization through a distributed graph-based agent.
Outcome: The proposed framework improves accuracy on real-world benchmarks and can be used to locate code snippets at a cost of 86%.
Multi-Prompting Decoder Helps Better Language Understanding (2025.findings-acl)

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Challenge: Existing methods to adapt Pre-trained Language Models to downstream tasks are limited by their inference APIs.
Approach: They propose a multi-prompting decoding framework that query PLMs with multiple prompts . they propose to query Plms with optimal transport for hidden states and calibrated decoding for class scores .
Outcome: The proposed framework achieves state-of-the-art results on multiple natural language understanding datasets under the few-shot setting.

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