--- title: "YongKang Liu — author profile and papers · Vision & language" description: "YongKang Liu, Northeastern University: 7 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them…" canonical: "https://research.elamur.ai/free/en/authors/yongkang-liu/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yongkang-liu/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / YongKang Liu # YongKang Liu YongKang Liu has 7 papers in our library, in 2026, most of them on [Vision & language](https://md.research.elamur.ai/free/en/topics/multimodal/), [Sentiment & emotion](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/), [Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/); often with [Daling Wang](https://md.research.elamur.ai/free/en/authors/daling-wang/), [Shi Feng](https://md.research.elamur.ai/free/en/authors/shi-feng/), [Xiaocui Yang](https://md.research.elamur.ai/free/en/authors/xiaocui-yang/). 7 papers in our library · 2026 [OpenAlex](https://openalex.org/A5139835859) · [**h-index 1**](https://openalex.org/authors/A5139835859) · [6 works](https://openalex.org/works?filter=author.id:A5139835859) · [1 citations](https://openalex.org/works?filter=author.id:A5139835859&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 7 works in our library](https://md.research.elamur.ai/free/en/authors/yongkang-liu/#papers) · [🔗 Cited 7 times in our library](https://md.research.elamur.ai/free/en/authors/yongkang-liu/cited-by/) · [⭐ Paper Stars ranking: #10093](https://md.research.elamur.ai/free/en/paper-stars/page/101/#star-10093) 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=YongKang+Liu) · [Semantic Scholar](https://www.semanticscholar.org/search?q=YongKang+Liu) · [dblp](https://dblp.org/search?q=YongKang+Liu) · [ACL Anthology](https://aclanthology.org/search/?q=YongKang+Liu) ## Affiliations [🎓**Northeastern University** Shenyang · China 2026 · 6 papers*current*](https://md.research.elamur.ai/free/en/universities/northeastern-university-cn/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 11 The field of science this work belongs to (OpenAlex fields).[Computer Science · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 7 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 6 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Information Systems · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Sociology and Political Science · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Philosophy · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/philosophy/) 🧭 Topics 5 Research subjects and languages the work is about.[Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/) · [Vision & language · 2 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Reasoning · 1 work](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Sentiment & emotion · 1 work](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) ## Works by year ### 2020s [**2026** 7 papers](https://md.research.elamur.ai/free/en/authors/yongkang-liu/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/)** *(2026 · 3 citations)* Most phone-scam detectors work on ASR transcripts. This means recognition errors carry through to the decision, and acoustic signals such as tone, stress or staged background noise are lost. SAFE-QAQ addresses this by running a large audio-language model (LALM) directly on raw call audio, so no transcription step is… 2. **[Why Do More Experts Fail? A Theoretical Analysis of Model Merging](https://md.research.elamur.ai/free/en/papers/wang-2026-why-do-more-experts-fail/)** *(2026 · 2 citations)* Merging several fine-tuned expert models into one multi-task model saves storage and compute. However, adding more experts stops helping quickly: state-of-the-art methods such as GENOME level off at around six merged models on most datasets. This paper asks why that ceiling exists. Using high-dimensional geometry… 3. **[MoLAN: A Unified Modality-Aware Noise Dynamic Editing Framework for Multimodal Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/xu-2026-molan-unified-modality-aware-noise/)** *(2026 · 1 citation)* Multimodal sentiment analysis (MSA) models often get misled by irrelevant visual or acoustic signals, such as background laughter that contradicts a speaker's mood. 4. **[NEAT: Neuron-Based Early Exit for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-neat-neuron-based-early-exit/)** *(2026 · 1 citation)* Large Reasoning Models frequently keep producing reasoning after they have already reached a correct solution. 5. **[PlaM: Training-Free Plateau-Guided Model Merging for Better Visual Grounding in MLLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plam-training-free-plateau-guided/)** *(2026 · 1 citation)* Multimodal instruction fine-tuning tends to weaken the text reasoning that MLLMs inherit from their base language models. 6. **[Look Within or Beyond? A Theoretical Comparison Between Parameter-Efficient and Full Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-look-within-or-beyond-theoretical/)** *(2026)* Parameter-efficient fine-tuning (PEFT) methods such as LoRA often match full fine-tuning (FFT) on standard benchmarks. It is less clear whether they hold up on harder tasks like reasoning and instruction-following, or under adversarial inputs. The authors address this with a theoretical analysis backed by experiments. 7. **[SAD: A Large-Scale Strategic Argumentative Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/liu-2026-sad-large-scale-strategic-argumentative/)** *(2026)* Most argument-generation corpora treat argumentation as a one-shot task: produce an argument for a topic or rebut a single claim. ## Co-authors here 12 of 17 co-authors with a page, the most papers together first. - [Daling Wang](https://md.research.elamur.ai/free/en/authors/daling-wang/) ×7 - [Shi Feng](https://md.research.elamur.ai/free/en/authors/shi-feng/) ×7 - [Xiaocui Yang](https://md.research.elamur.ai/free/en/authors/xiaocui-yang/) ×5 - [Hinrich Schuetze](https://md.research.elamur.ai/free/en/authors/hinrich-schuetze/) ×4 - [Ercong Nie](https://md.research.elamur.ai/free/en/authors/ercong-nie/) ×3 - [Xingle Xu](https://md.research.elamur.ai/free/en/authors/xingle-xu/) ×3 - [Yifei Zhang](https://md.research.elamur.ai/free/en/authors/yifei-zhang/) ×3 - [Zijing Wang](https://md.research.elamur.ai/free/en/authors/zijing-wang/) ×3 - [Mingyang Wang](https://md.research.elamur.ai/free/en/authors/mingyang-wang/) ×2 - [Peidong Wang](https://md.research.elamur.ai/free/en/authors/peidong-wang/) ×2 - [Yiqun Zhang](https://md.research.elamur.ai/free/en/authors/yiqun-zhang/) ×2 - [Kaisong Song](https://md.research.elamur.ai/free/en/authors/kaisong-song/) ## 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/) ×4: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×4 - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×3: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×3 ## Cited by Papers of our library cite their works 7 times (of the 149,439 papers whose bibliographies we read); [2 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/yongkang-liu/cited-by/). Updated 1 November 2026