Jinghui Qin
Jinghui Qin has 3 papers in our library, in 2020–2022, most of them on Reasoning, Question answering, Dialogue systems; often with Liang Lin, Xiaodan Liang, Jiaqi Chen.
OpenAlex · ORCID · h-index 20 · 106 works · 1,266 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 201 times in our library · ⭐ Paper Stars ranking: #3600
Affiliations
Concepts, shelves and topics
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksMathematics · 2 worksApplied Mathematics · 2 worksComputational Theory and Mathematics · 2 worksComputer Vision and Pattern Recognition · 2 worksArtificial Intelligence · 1 workArts and Humanities · 1 workLanguage and Linguistics · 1 work
🧭 Topics 5Research subjects and languages the work is about.Reasoning · 2 worksDialogue systems · 1 workEvaluation & benchmarks · 1 workQuestion answering · 1 workVision & language · 1 work
Works by year
2020s
Papers
- GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning (2021 · 183 citations)
Automated solving of geometry problems requires a system to interpret a diagram, connect it to the accompanying text, and apply theorems. - GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems (2020 · 144 citations)
Open-domain chatbots are hard to evaluate automatically. Overlap metrics such as BLEU and learned scorers such as ADEM, RUBER and BERT-RUBER match human ratings of coherence poorly. They also ignore how topics shift between context and response. GRADE (Graph-enhanced Representations for Automatic Dialogue Evaluation)… - UniGeo: Unifying Geometry Logical Reasoning via Reformulating Mathematical Expression (2022 · 111 citations)
Neural geometry solvers usually handle numerical calculation and formal proving as separate tasks, even though both rely on shared geometric knowledge.
Co-authors here
Venues
- Conference on Empirical Methods in Natural Language Processing (EMNLP) ×2: EMNLP 2022, EMNLP 2020
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2021
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