--- title: "Yiwei Wang — author profile and papers — Elamur Research" description: "Yiwei Wang, University of California, Merced: 13 papers on Elamur Research (2025–2026), h-index 5 — affiliations, topics, co-authors and…" canonical: "https://research.elamur.ai/free/en/authors/yiwei-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yiwei-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Yiwei Wang # Yiwei Wang Yiwei Wang has 13 papers in our library, in 2025–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/), [Bias, fairness & safety](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/); often with [Yujun Cai](https://md.research.elamur.ai/free/en/authors/yujun-cai/), [Baolong Bi](https://md.research.elamur.ai/free/en/authors/baolong-bi/), [Lingrui Mei](https://md.research.elamur.ai/free/en/authors/lingrui-mei/). 13 papers in our library · 2025–2026 [OpenAlex](https://openalex.org/A5100397321) · [ORCID](https://orcid.org/0000-0003-0267-2102) · [**h-index 5**](https://openalex.org/authors/A5100397321) · [35 works](https://openalex.org/works?filter=author.id:A5100397321) · [103 citations](https://openalex.org/works?filter=author.id:A5100397321&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 13 works in our library](https://md.research.elamur.ai/free/en/authors/yiwei-wang/#papers) · [🔗 Cited 71 times in our library](https://md.research.elamur.ai/free/en/authors/yiwei-wang/cited-by/) · [⭐ Paper Stars ranking: #7071](https://md.research.elamur.ai/free/en/paper-stars/page/71/#star-7071) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Yiwei+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Yiwei+Wang) · [dblp](https://dblp.org/search?q=Yiwei+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Yiwei+Wang) ## Affiliations [🎓**University of California, Merced** Merced · United States 2024–2026 · 15 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-merced/) · [🎓**University of California, Los Angeles** Los Angeles · United States 2024–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-california-los-angeles/) · [🎓**Rutgers, The State University of New Jersey** New Brunswick · United States 2016–2018 · 6 papers](https://md.research.elamur.ai/free/en/universities/rutgers-the-state-university-of-new-jersey/) · [🎓**Shandong Normal University** Jinan · China 2022–2025 · 3 papersEducation 2022–2025 · 硕士, School of Information Science and Engineering](https://ror.org/01wy3h363) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 7 more institutions on single bylines are not listed. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 13 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 11 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 11 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 11 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/) · [Information Systems · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Control and Systems Engineering · 1 work](https://md.research.elamur.ai/free/en/shelves/engineering/control-and-systems-engineering/) · [Software · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/software/) · [Signal Processing · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/signal-processing/) 🧭 Topics 8 Research subjects and languages the work is about.[Language models & pretraining · 5 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Reasoning · 4 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Bias, fairness & safety · 2 works](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Interpretability · 1 work](https://md.research.elamur.ai/free/en/topics/interpretability/) · [Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/) · [Vision & language · 1 work](https://md.research.elamur.ai/free/en/topics/multimodal/) ## Works by year ### 2020s [**2026** 6 papers](https://md.research.elamur.ai/free/en/authors/yiwei-wang/year/2026/) · [**2025** 7 papers](https://md.research.elamur.ai/free/en/authors/yiwei-wang/year/2025/) ## Papers The most cited first (OpenAlex and our library). 1. **[Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-mitigating-lost-retrieval-problems-retrieval/)** *(2025 · 16 citations)* In retrieval-augmented multi-hop QA, LLMs often split a complex question into sub-questions. Later sub-questions then refer to an earlier result through a pronoun such as "this author" instead of naming the entity. The authors call this failure "lost-in-retrieval." Without the key entity, retrieval for these… 2. **[METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/li-2025-metal-multi-agent-framework-chart/)** *(2025 · 15 citations)* The paper addresses chart-to-code generation: given an image of a reference chart, a model must write plotting code (e.g., Python) whose rendered output reproduces the chart's type, layout, colors and text. 3. **[Can Graph Descriptive Order Affect Solving Graph Problems with LLMs?](https://md.research.elamur.ai/free/en/papers/ge-2025-can-graph-descriptive-order-affect/)** *(2025 · 10 citations)* Studies of LLM graph reasoning usually turn a graph into text by listing its edges in an arbitrary sequence. 4. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/)** *(2026 · 9 citations)* Most earlier reviews of mechanistic interpretability (MI) in LLMs describe what researchers have discovered inside models. 5. **[DiMo-GUI: Advancing Test-time Scaling in GUI Grounding via Modality-Aware Visual Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2025-dimo-gui-advancing-test-time/)** *(2025 · 8 citations)* Locating the on-screen element that a natural-language command refers to (GUI grounding) is difficult. High-resolution screenshots are crowded with distractors, and vision-language models tend to favour visible text over icons, even when an icon is the real target. DiMo-GUI is a training-free, plug-and-play inference… 6. **[Thinking with Sound: Audio Chain-of-Thought Enables Multimodal Reasoning in Large Audio-Language Models](https://md.research.elamur.ai/free/en/papers/xiong-2025-thinking-sound-audio-chain-thought/)** *(2025 · 6 citations)* Large Audio-Language Models (LALMs) turn a recording into a fixed set of embeddings once. After that step they cannot go back to the signal. Because of this, they perform poorly when audio is noisy or degraded, or when a task depends on fine acoustic detail. The authors propose Thinking-with-Sound (TwS), a framework… 7. **[Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/xiong-2025-mapping-minds-llms-graph-based/)** *(2025 · 5 citations)* Large Reasoning Models (LRMs) such as DeepSeek-R1 produce long Chain-of-Thought traces, yet they often behave erratically. 8. **[Vulnerability of LLMs to Vertically Aligned Text Manipulations](https://md.research.elamur.ai/free/en/papers/li-2025-vulnerability-llms-vertically-aligned-text/)** *(2025 · 5 citations)* The paper asks whether decoder-based LLMs are as vulnerable as encoder models like BERT when some words in a text are written vertically, one character per line. 9. **[Gated Differentiable Working Memory for Long-Context Language Modeling](https://md.research.elamur.ai/free/en/papers/mei-2026-gated-differentiable-working-memory-long/)** *(2026 · 4 citations)* Long inputs remain difficult for transformer LLMs. Attention spreads thin over thousands of tokens, and evidence placed mid-document is often overlooked. Test-time training methods such as qTTT address this by briefly fine-tuning "fast weights" on the given context. However, they sample positions uniformly, so they… 10. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/)** *(2026 · 4 citations)* Safety alignment in LLMs usually works as a yes/no gate: a prompt is either answered or refused. This tends to block harmless requests, such as a "killer slideshow," and to miss subtle or context-dependent harm. The authors propose HiddenGuard, which moderates output token by token instead of refusing whole answers. 11. **[a1: Steep Test-time Scaling Law via Environment Augmented Generation](https://md.research.elamur.ai/free/en/papers/mei-2026-a1-steep-test-time-scaling/)** *(2026 · 2 citations)* LLMs often fail at long multi-step reasoning. They usually generate a whole solution in one pass with no intermediate checks, so an early mistake carries through to the final answer. The authors propose Environment Augmented Generation (EAG), which casts reasoning as a Markov Decision Process. While generating, the… 12. **[Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/song-2026-hard-read-easy-jailbreak-how/)** *(2026)* Vision-based context compression, as in DeepSeek-OCR and Glyph, renders long text as images so that a model needs fewer tokens. 13. **[Mitigating Coordinate Prediction Bias from Positional Encoding Failures](https://md.research.elamur.ai/free/en/papers/tao-2026-mitigating-coordinate-prediction-bias-positional/)** *(2026)* Multimodal LLMs that output click coordinates as digit strings often drift on high-resolution screenshots, because visual positional encodings (VPEs) lose grounding strength in long visual contexts. ## Co-authors here 12 of 29 co-authors with a page, the most papers together first. - [Yujun Cai](https://md.research.elamur.ai/free/en/authors/yujun-cai/) ×5 - [Baolong Bi](https://md.research.elamur.ai/free/en/authors/baolong-bi/) ×4 - [Lingrui Mei](https://md.research.elamur.ai/free/en/authors/lingrui-mei/) ×4 - [Shenghua Liu](https://md.research.elamur.ai/free/en/authors/shenghua-liu/) ×4 - [Xueqi Cheng](https://md.research.elamur.ai/free/en/authors/xueqi-cheng/) ×4 - [Yuyao Ge](https://md.research.elamur.ai/free/en/authors/yuyao-ge/) ×3 - [Zhecheng Li](https://md.research.elamur.ai/free/en/authors/zhecheng-li/) ×3 - [Zhen Xiong](https://md.research.elamur.ai/free/en/authors/zhen-xiong/) ×3 - [Jun Wan](https://md.research.elamur.ai/free/en/authors/jun-wan/) ×2 - [Kai-Wei Chang](https://md.research.elamur.ai/free/en/authors/kai-wei-chang/) ×2 - [Nanyun Peng](https://md.research.elamur.ai/free/en/authors/nanyun-peng/) ×2 - [Bingxuan Li](https://md.research.elamur.ai/free/en/authors/bingxuan-li/) ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/) ×6: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×2, [ACL 2025](https://md.research.elamur.ai/free/en/venues/acl/2025/) ×4 - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×4: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×4 - [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/) ×2: [EMNLP 2025](https://md.research.elamur.ai/free/en/venues/emnlp/2025/) ×2 ## Cited by Papers of our library cite their works 71 times (of the 149,439 papers whose bibliographies we read); [20 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yiwei-wang/cited-by/). Updated 1 November 2026