Yuanzhuo Wang
Yuanzhuo Wang has 6 papers in our library, in 2024–2026, most of them on Language models & pretraining, Evaluation & benchmarks, Vision & language; often with Fei Sun, Hexiang Tan, Xueqi Cheng.
OpenAlex · ORCID · Wikidata · h-index 26 · 197 works · 3,481 citations OpenAlex, 2026-10-14
📄 6 works in our library · 🔗 Cited 182 times in our library · 7 more in our library without a page yet · ⭐ Paper Stars ranking: #7788
Affiliations
Fields, topics and concepts
📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 6 worksComputer Science · 6 worksArtificial Intelligence · 6 worksLanguage and Linguistics · 6 worksComputer Vision and Pattern Recognition · 4 worksInformation Systems · 1 work
🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 3 worksEvaluation & benchmarks · 2 worksVision & language · 2 worksMultilingual & cross-lingual NLP · 1 workText generation · 1 work
Works by year
2020s
Papers
- Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts? (2024 · 37 citations)
Hybrid question-answering systems give an LLM two kinds of context: passages it wrote itself and passages retrieved from an external corpus such as Wikipedia. - 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… - 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. - DataArc-SynData-Toolkit: A Unified Closed-Loop Framework for Multi-Path, Multimodal, and Multilingual Data Synthesis (2026)
Synthetic data can ease data shortages for LLMs in specialised domains and low-resource languages, but current tools tend to be hard for non-experts, rely on inconsistent data formats, and handle extra modalities or languages poorly. - FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation (2026)
Generative MLLMs that interleave images and text can produce content that looks authoritative but contains factual errors. - JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM Evaluation (2026)
Static benchmarks for LLMs saturate quickly, cover a fixed slice of knowledge, risk contamination, and pose questions whose difficulty may not suit the model under test.
All works
- Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learning ↗International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) · no summary yetZixuan Li et al.2021 · 409 citations
- Document Embedding Enhanced Event Detection with Hierarchical and Supervised Attention ↗Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · no summary yetYue Zhao et al.2018 · 146 citations
- Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs ↗Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yetZixuan Li et al.2021 · 124 citations
- Improving Neural Abstractive Document Summarization with Explicit Information Selection Modeling ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetWei Li et al.2018 · 79 citations
- NeuInfer: Knowledge Inference on N-ary Facts ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetSaiping Guan et al.2020 · 78 citations
- Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts?Annual Meeting of the Association for Computational Linguistics (ACL)Hexiang Tan, Fei Sun, Wanli Yang, et al.2024 · 37 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
- 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
- FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Yubo Shan, Kun Zhang, Qiming Xu, et al.2026
- JudgeAgent: Beyond Static Benchmarks for Knowledge-Driven and Dynamic LLM EvaluationFindings of the Association for Computational LinguisticsZhichao Shi, Xuhui Jiang, Chengjin Xu, et al.2026
- Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetTian Xueyun et al.2026
- ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetTian Xueyun et al.2026
Co-authors here
- Fei Sun ×3
- Hexiang Tan ×3
- Xueqi Cheng ×3
- Chengjin Xu ×2
- Du Su ×2
- Jian Guo ×2
- Jingang Wang ×2
- Qi Cao ×2
- Wanli Yang ×2
- Xin Chen ×2
- Xuhui Jiang ×2
- Zhichao Shi ×2
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×7: ACL 2026 ×3, ACL 2024
- Conference on Empirical Methods in Natural Language Processing (EMNLP) ×2: EMNLP 2025
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- Findings of the Association for Computational Linguistics: ACL 2026
- International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)
- Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
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