Junjue Wang
Junjue Wang has 3 papers in our library, in 2025–2026, most of them on Language models & pretraining, Reasoning, Multilingual & cross-lingual NLP; often with Heli Qi, Qingcheng Zeng, Weihao Xuan.
OpenAlex · ORCID · h-index 28 · 85 works · 3,581 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 74 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #7006
Affiliations
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksArts and Humanities · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works
🧭 Topics 5Research subjects and languages the work is about.Language models & pretraining · 2 worksReasoning · 2 worksEvaluation & benchmarks · 1 workMultilingual & cross-lingual NLP · 1 workVision & language · 1 work
Works by year
2020s
Papers
- MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation (2025 · 75 citations)
Evaluating LLMs across languages has two gaps. Demanding reasoning benchmarks such as MMLU-Pro exist mainly in English. Multilingual suites like Global-MMLU combine translation sources of uneven quality and pose easier questions. The authors address both with MMLU-ProX, which carries the ten-option, reasoning-heavy… - Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language Models (2025 · 11 citations)
Vision-language models (VLMs) can state in plain language how sure they are of an answer. This study asks whether that stated confidence actually tracks how often they are correct. The authors evaluate verbalized calibration across three model families: instruction-tuned, text-reasoning, and visual-reasoning… - The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use Agents (2026 · 2 citations)
The paper asks whether tool use always worsens how well LLM agents' stated confidence matches their real accuracy, or whether the effect depends on the tool.
All works
- FarSeg++: Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery ↗IEEE Transactions on Pattern Analysis and Machine Intelligence · no summary yetZhuo Zheng et al.2023 · 93 citations
- MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model EvaluationConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Rui Yang, Heli Qi, et al.2025 · 75 citations
- Seeing is Believing, but How Much? A Comprehensive Analysis of Verbalized Calibration in Vision-Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2025 · 11 citations
- The Confidence Dichotomy: Analyzing and Mitigating Miscalibration in Tool-Use AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Weihao Xuan, Qingcheng Zeng, Heli Qi, et al.2026 · 2 citations
- Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations ↗arXiv (Cornell University) · no summary yetJunjue Wang et al.2026
Co-authors here
- Heli Qi ×3
- Qingcheng Zeng ×3
- Weihao Xuan ×3
- Naoto Yokoya ×2
- Yunze Xiao ×2
- Aosong Feng
- Fan Gao
- Jinghui Lu
- Rui Yang
Venues
- Conference on Empirical Methods in Natural Language Processing (EMNLP) ×2: EMNLP 2025 ×2
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- IEEE Transactions on Pattern Analysis and Machine Intelligence
Cited by
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