Jiannan Cao
Jiannan Cao has 3 papers in our library, in 2024–2026, most of them on Coreference resolution, Language models & pretraining, Reasoning; often with Jianwei Yin, Xinyue Peng, Xuhong Zhang.
OpenAlex · h-index 2 · 7 works · 7 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 15 times in our library · ⭐ Paper Stars ranking: #8991
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 workInformation Systems · 1 work
🧭 Topics 4Research subjects and languages the work is about.Coreference resolution · 1 workLanguage models & pretraining · 1 workGPU & parallel computing · 1 workReasoning · 1 work
Works by year
2020s
Papers
- Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding (2024 · 10 citations)
LLMs still struggle with long inputs. When a document uses many pronouns, modifiers and varied noun phrases for the same entities, models lose track of the referents, especially in mid-document passages. The authors propose Long Question Coreference Adaptation (LQCA), a preprocessing pipeline that rewrites the… - EquiBench: Benchmarking Large Language Models' Reasoning about Program Semantics via Equivalence Checking (2025 · 8 citations)
EquiBench asks whether large language models actually grasp what code does or mostly react to how it looks. - ToolGate: Contract-Grounded and Verified Tool Execution for LLMs (2026 · 3 citations)
LLM agents that call external APIs usually decide in free-form text when a tool may be used and whether its output can be trusted.
Co-authors here
- Jianwei Yin ×2
- Xinyue Peng ×2
- Xuhong Zhang ×2
- Yanming Liu ×2
- Diyi Yang
- Hongyu Chen
- Jintao Chen
- Ke Wang
- Ran Li
- Tianyu Du
- Xinyi Wang
- Xun Wang
Venues
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
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