Jingang Wang
Jingang Wang has 7 papers in our library, in 2022–2026, most of them on Language models & pretraining, Dialogue systems, Reasoning; often with Fei Sun, Xin Chen, Xueqi Cheng.
OpenAlex · h-index 1 · 20 works · 1 citations OpenAlex, 2026-10-14
📄 7 works in our library · 🔗 Cited 124 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #4391
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 7 worksComputer Science · 7 worksArtificial Intelligence · 7 worksLanguage and Linguistics · 7 worksComputer Vision and Pattern Recognition · 2 worksInformation Systems · 1 work
🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 worksDialogue systems · 2 worksEvaluation & benchmarks · 1 workInformation retrieval & search · 1 work
Works by year
2020s
Papers
- Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification (2022 · 362 citations)
Prompt-tuning turns text classification into a masked language modeling task. A template wraps the input, and a verbalizer maps predicted words at the [MASK] position to class labels. Verbalizers are usually handcrafted with a single class-name word or learned from data. Hand-built ones cover too few words and carry… - Too Consistent to Detect: A Study of Self-Consistent Errors in LLMs (2025 · 12 citations)
LLM error detectors often treat agreement across sampled answers as a sign of correctness. This paper identifies a blind spot in that assumption: self-consistent errors , where a model gives the same wrong answer, up to semantic equivalence, in its greedy output and in all stochastic samples. The authors define these… - Sibyl: Empowering Empathetic Dialogue Generation in Large Language Models via Sensible and Visionary Commonsense Inference (2025 · 9 citations)
LLM-based chatbots often fall short on empathy and emotional support in multi-turn conversations, even when they are given commonsense knowledge. - The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics Analysis (2026 · 6 citations)
Reasoning LLMs often keep generating "thinking" tokens after they already have enough information to answer, which wastes compute and is known as overthinking. - Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from Text (2026 · 4 citations)
Training LLM agents for multi-turn tool use is limited by a shortage of realistic trajectories. Most existing synthesis methods start from a fixed API collection, so the data can only be as broad as that collection. The authors invert this approach. They argue that ordinary web text, such as how-to guides and… - BaseCal: Unsupervised Confidence Calibration via Base Model Signals (2026 · 1 citation)
Post-trained LLMs (PoLLMs), such as instruction-tuned or RLHF-aligned models, tend to be overconfident: they assign high probability even to wrong answers, which limits the usefulness of confidence for detecting hallucinations. - MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks (2026)
Conversational retrieval decides which evidence a RAG system can use, but its benchmarks have two kinds of flaws.
All works
- Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Shengding Hu, Ning Ding, Huadong Wang, et al.2022 · 362 citations
- Too Consistent to Detect: A Study of Self-Consistent Errors in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Hexiang Tan, Fei Sun, Sha Liu, et al.2025 · 12 citations
- Sibyl: Empowering Empathetic Dialogue Generation in Large Language Models via Sensible and Visionary Commonsense InferenceInternational Conference on Computational Linguistics (COLING)Lanrui Wang, Jiangnan Li, Chenxu Yang, et al.2025 · 9 citations
- The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics AnalysisAnnual Meeting of the Association for Computational Linguistics (ACL)Zihao Wei, Liang Pang, Jiahao Liu, et al.2026 · 6 citations
- Unlocking Implicit Experience: Synthesizing Tool-Use Trajectories from TextAnnual Meeting of the Association for Computational Linguistics (ACL)Zhihao Xu, Rumei Li, Jiahuan Li, et al.2026 · 4 citations
- BaseCal: Unsupervised Confidence Calibration via Base Model SignalsAnnual Meeting of the Association for Computational Linguistics (ACL)Hexiang Tan, Wanli Yang, Junwei Zhang, et al.2026 · 1 citation
- MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval BenchmarksAnnual Meeting of the Association for Computational Linguistics (ACL)Junhao Ruan, Abudukeyumu Abudula, Bei Li, et al.2026
- LinkQA: Synthesizing Diverse QA from Multiple Seeds Strongly Linked by Knowledge Points ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetXuemiao Zhang et al.2026
Co-authors here
- Fei Sun ×3
- Xin Chen ×3
- Xueqi Cheng ×3
- Xunliang Cai ×3
- Du Su ×2
- Hexiang Tan ×2
- Huawei Shen ×2
- Yuanzhuo Wang ×2
- Bei Li
- Huan Liu
- Jiahao Liu
- Jiahuan Li
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×6: ACL 2026 ×4, ACL 2022
- International Conference on Computational Linguistics (COLING): COLING 2025
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
Cited by
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