--- title: "Daling Wang — author profile and papers · Vision & language" description: "Daling Wang, Northeastern University: 11 papers on Elamur Research (2026), h-index 23 — affiliations, topics, co-authors and who cites…" canonical: "https://research.elamur.ai/free/en/authors/daling-wang/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/daling-wang/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Daling Wang # Daling Wang Daling Wang has 11 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/), [Reasoning](https://md.research.elamur.ai/free/en/topics/reasoning/); often with [Shi Feng](https://md.research.elamur.ai/free/en/authors/shi-feng/), [Xiaocui Yang](https://md.research.elamur.ai/free/en/authors/xiaocui-yang/), [YongKang Liu](https://md.research.elamur.ai/free/en/authors/yongkang-liu/). 11 papers in our library · 2026 [OpenAlex](https://openalex.org/A5035378456) · [ORCID](https://orcid.org/0000-0003-1340-0778) · [**h-index 23**](https://openalex.org/authors/A5035378456) · [215 works](https://openalex.org/works?filter=author.id:A5035378456) · [2,166 citations](https://openalex.org/works?filter=author.id:A5035378456&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 11 works in our library](https://md.research.elamur.ai/free/en/authors/daling-wang/#papers) · [🔗 Cited 47 times in our library](https://md.research.elamur.ai/free/en/authors/daling-wang/cited-by/) · [4 more in our library without a page yet](#also) · [⭐ Paper Stars ranking: #9865](https://md.research.elamur.ai/free/en/paper-stars/page/99/#star-9865) 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=Daling+Wang) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Daling+Wang) · [dblp](https://dblp.org/search?q=Daling+Wang) · [ACL Anthology](https://aclanthology.org/search/?q=Daling+Wang) ## Affiliations [🎓**Northeastern University** Shenyang · China 2000–2026 · 177 papers*current*](https://md.research.elamur.ai/free/en/universities/northeastern-university-cn/) · [🎓**Northeastern University** Boston · United States 2009–2026 · 28 papers*current*](https://md.research.elamur.ai/free/en/universities/northeastern-university/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 3 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 15 The field of science this work belongs to (OpenAlex fields).[Computer Science · 11 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Artificial Intelligence · 10 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Language and Linguistics · 8 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Information Systems · 4 works](https://md.research.elamur.ai/free/en/shelves/computer-science/information-systems/) · [Psychology · 3 works](https://md.research.elamur.ai/free/en/shelves/psychology/) · [Experimental and Cognitive Psychology · 2 works](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Social Sciences · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/) · [Medicine · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/) · [Sociology and Political Science · 1 work](https://md.research.elamur.ai/free/en/shelves/social-sciences/sociology-and-political-science/) · [Health Informatics · 1 work](https://md.research.elamur.ai/free/en/shelves/medicine/health-informatics/) · [Applied Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/applied-psychology/) · [Philosophy · 1 work](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/philosophy/) · [Social Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/social-psychology/) 🧭 Topics 8 Research subjects and languages the work is about.[Vision & language · 3 works](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Speech & spoken language · 1 work](https://md.research.elamur.ai/free/en/topics/speech/) · [Reasoning · 2 works](https://md.research.elamur.ai/free/en/topics/reasoning/) · [Sentiment & emotion · 2 works](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Dialogue systems · 1 work](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Information retrieval & search · 1 work](https://md.research.elamur.ai/free/en/topics/information-retrieval/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) · [Question answering · 1 work](https://md.research.elamur.ai/free/en/topics/question-answering/) ## Works by year ### 2020s [**2026** 11 papers](https://md.research.elamur.ai/free/en/authors/daling-wang/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. **[DeepMed: Building a Medical DeepResearch Agent via Multi-hop Med-Search Data and Turn-Controlled Agentic Training & Inference](https://md.research.elamur.ai/free/en/papers/wang-2026-deepmed-building-medical-deepresearch-agent/)** *(2026 · 1 citation)* General-purpose DeepResearch (DR) agents, which interleave web search with reasoning, improve only modestly when moved to medicine. 4. **[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. 5. **[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. 6. **[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. 7. **[Resource-Limited Joint Multimodal Sentiment Reasoning and Classification via Chain-of-Thought Enhancement and Distillation](https://md.research.elamur.ai/free/en/papers/shangguan-2026-resource-limited-joint-multimodal-sentiment/)** *(2026 · 1 citation)* The paper tackles multimodal sentiment analysis of text-image posts when only a small model can be deployed. 8. **[CIRAG: Construction–Integration Retrieval and Adaptive Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/wei-2026-cirag-construction-integration-retrieval-adaptive/)** *(2026)* Triple-based iterative RAG for multi-hop QA has two weaknesses. It keeps only one best triple per step, so early mistakes compound and parallel evidence is lost. It also uses a single evidence granularity, which can be too noisy or too sparse depending on the question. CIRAG draws on Kintsch's… 9. **[GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing](https://md.research.elamur.ai/free/en/papers/wang-2026-genpt-beyond-self-report-reliable/)** *(2026)* Psychological profiling of persona-conditioned LLM agents (PC-Agents) usually relies on self-report questionnaires such as BFI, BDI or MBTI. 10. **[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. 11. **[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. ## All works 15 works of theirs in our library, the most cited first; 11 with a page here, the others link their original until we summarise them. 1. **[Multimodal Sentiment Detection Based on Multi-channel Graph Neural Networks ↗](https://aclanthology.org/2021.acl-long.28/) 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 yet**Xiaocui Yang et al.*2021 · 147 citations* 2. **[A Co-Attention Neural Network Model for Emotion Cause Analysis with Emotional Context Awareness ↗](https://aclanthology.org/D18-1506/) Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yet**Xiangju Li et al.*2018 · 140 citations* 3. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations* 4. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijing Wang, Xingle Xu, YongKang Liu, et al.*2026 · 2 citations* 5. **[DeepMed: Building a Medical DeepResearch Agent via Multi-hop Med-Search Data and Turn-Controlled Agentic Training & Inference](https://md.research.elamur.ai/free/en/papers/wang-2026-deepmed-building-medical-deepresearch-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Hao Wang, Shi Feng, et al.*2026 · 1 citation* 6. **[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/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingle Xu, YongKang Liu, Dexian Cai, et al.*2026 · 1 citation* 7. **[NEAT: Neuron-Based Early Exit for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-neat-neuron-based-early-exit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Liu, YongKang Liu, Xiaocui Yang, et al.*2026 · 1 citation* 8. **[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/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zijing Wang, YongKang Liu, Mingyang Wang, et al.*2026 · 1 citation* 9. **[Resource-Limited Joint Multimodal Sentiment Reasoning and Classification via Chain-of-Thought Enhancement and Distillation](https://md.research.elamur.ai/free/en/papers/shangguan-2026-resource-limited-joint-multimodal-sentiment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haonan Shangguan, Xiaocui Yang, Shi Feng, et al.*2026 · 1 citation* 10. **[CIRAG: Construction–Integration Retrieval and Adaptive Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/wei-2026-cirag-construction-integration-retrieval-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zili Wei, Yilin Wang, Xiaocui Yang, et al.*2026* 11. **[GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing](https://md.research.elamur.ai/free/en/papers/wang-2026-genpt-beyond-self-report-reliable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Wang, Shuang Wu, Bixuan Wang, et al.*2026* 12. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Xingle Xu, Ercong Nie, et al.*2026* 13. **[SAD: A Large-Scale Strategic Argumentative Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/liu-2026-sad-large-scale-strategic-argumentative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YongKang Liu, Jiayang Yu, Mingyang Wang, et al.*2026* 14. **[RATION: Entropy-Driven Task-Adaptive Visual Attention Allocation Framework for Multimodal Reasoning ↗](https://aclanthology.org/2026.findings-acl.1238/) Findings of the Association for Computational Linguistics: ACL 2026 · no summary yet**Xingle Xu et al.*2026* 15. **[MTRouter: Cost-Aware Multi-Turn LLM Routing with History–Model Joint Embeddings ↗](https://aclanthology.org/2026.acl-long.2045/) Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yet**Yiqun Zhang et al.*2026* ## Co-authors here 12 of 26 co-authors with a page, the most papers together first. - [Shi Feng](https://md.research.elamur.ai/free/en/authors/shi-feng/) ×11 - [Xiaocui Yang](https://md.research.elamur.ai/free/en/authors/xiaocui-yang/) ×9 - [YongKang Liu](https://md.research.elamur.ai/free/en/authors/yongkang-liu/) ×7 - [Yifei Zhang](https://md.research.elamur.ai/free/en/authors/yifei-zhang/) ×6 - [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 - [Yiqun Zhang](https://md.research.elamur.ai/free/en/authors/yiqun-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 - [Zihan Wang](https://md.research.elamur.ai/free/en/authors/zihan-wang/) ×2 ## 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/) ×7: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×6 - [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/) ×5: [Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/) ×5 - Findings of the Association for Computational Linguistics: ACL 2026 - Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing - 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) ## Cited by Papers of our library cite their works 47 times (of the 149,439 papers whose bibliographies we read); [7 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/daling-wang/cited-by/). Updated 1 November 2026