Papers with Identification
SpeciaLex: A Benchmark for In-Context Specialized Lexicon Learning (2024.findings-emnlp)
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| Challenge: | Specialized lexicons are collections of words with associated constraints such as special definitions, specific roles, and intended target audiences. |
| Approach: | They propose a benchmark to evaluate a language model’s ability to follow specialized lexicon-based constraints across 18 diverse subtasks with 1,785 test instances covering core tasks of Checking, Identification, Rewriting, and Open Generation. |
| Outcome: | The proposed model can follow specialized lexicon-based constraints across 18 diverse subtasks with 1,785 test instances covering core tasks Checking, Identification, Rewriting, and Open Generation. |
COAST: Enhancing the Code Debugging Ability of LLMs through Communicative Agent Based Data Synthesis (2025.findings-naacl)
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Weiqing Yang, Hanbin Wang, Zhenghao Liu, Xinze Li, Yukun Yan, Shuo Wang, Yu Gu, Minghe Yu, Zhiyuan Liu, Ge Yu
| Challenge: | Existing code debugging benchmarks focus on the Code Repair stage of the code generation process. |
| Approach: | They propose a framework to evaluate the debugging abilities of large language models by emulating the human debug process. |
| Outcome: | The proposed framework outperforms human-curated and GPT-4-generated training data, enabling 7B-scale LLMs to achieve comparable debugging performance to GPT-3.5. |
A Unified Generative Framework for Bilingual Euphemism Detection and Identification (2024.findings-acl)
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| Challenge: | Existing euphemism datasets are only domain-specific or language-specific. |
| Approach: | They propose a unified model to jointly conduct bilingual euphemism detection and identification tasks. |
| Outcome: | The proposed model is effective and provides a new reference standard for euphemism detection and identification. |