--- title: "Kai Xiong — author profile and papers — Elamur Research" description: "Kai Xiong, Harbin Institute of Technology: 6 papers on Elamur Research (2023–2026), h-index 0 — affiliations, topics, co-authors and who…" canonical: "https://research.elamur.ai/free/en/authors/kai-xiong/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/kai-xiong/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Kai Xiong # Kai Xiong Kai Xiong has 6 papers in our library, in 2023–2026, most of them on [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Xiao Ding](https://md.research.elamur.ai/free/en/authors/xiao-ding/), [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/), [Ting Liu](https://md.research.elamur.ai/free/en/authors/ting-liu/). 6 papers in our library · 2023–2026 [OpenAlex](https://openalex.org/A5139822121) · [**h-index 0**](https://openalex.org/authors/A5139822121) · [8 works](https://openalex.org/works?filter=author.id:A5139822121) · [0 citations](https://openalex.org/works?filter=author.id:A5139822121&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 6 works in our library](https://md.research.elamur.ai/free/en/authors/kai-xiong/#papers) · [🔗 Cited 54 times in our library](https://md.research.elamur.ai/free/en/authors/kai-xiong/cited-by/) · [⭐ Paper Stars ranking: #8019](https://md.research.elamur.ai/free/en/paper-stars/page/81/#star-8019) 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=Kai+Xiong) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Kai+Xiong) · [dblp](https://dblp.org/search?q=Kai+Xiong) · [ACL Anthology](https://aclanthology.org/search/?q=Kai+Xiong) ## Affiliations [🎓**Harbin Institute of Technology** Harbin · China 2026 · 3 papers*current*](https://md.research.elamur.ai/free/en/universities/harbin-institute-of-technology/) 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 10 The field of science this work belongs to (OpenAlex fields).[Computer Science · 6 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Arts and Humanities · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Artificial Intelligence · 5 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Language and Linguistics · 5 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Computer Vision and Pattern Recognition · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/computer-vision-and-pattern-recognition/) · [Cognitive Neuroscience · 1 work](https://md.research.elamur.ai/free/en/shelves/neuroscience/cognitive-neuroscience/) · [Experimental and Cognitive Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/experimental-and-cognitive-psychology/) · [Human-Computer Interaction · 1 work](https://md.research.elamur.ai/free/en/shelves/computer-science/human-computer-interaction/) · [Neuroscience · 1 work](https://md.research.elamur.ai/free/en/shelves/neuroscience/) · [Psychology · 1 work](https://md.research.elamur.ai/free/en/shelves/psychology/) 🧭 Topics 2 Research subjects and languages the work is about.[Language models & pretraining · 2 works](https://md.research.elamur.ai/free/en/topics/language-models/) · [Evaluation & benchmarks · 2 works](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) ## Works by year ### 2020s [**2026** 5 papers](https://md.research.elamur.ai/free/en/authors/kai-xiong/year/2026/) · [**2023** 1 paper](https://md.research.elamur.ai/free/en/authors/kai-xiong/year/2023/) ## Papers The most cited first (OpenAlex and our library). 1. **[Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate](https://md.research.elamur.ai/free/en/papers/xiong-2023-examining-inter-consistency-large-language/)** *(2023 · 94 citations)* Work on LLM consistency usually examines a single model. This paper asks whether several LLMs can work together and agree on a shared answer. The authors use multi-choice commonsense reasoning as a testbed because disagreement between models can be measured exactly. They define a metric, INCON, which is the share of… 2. **[MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization](https://md.research.elamur.ai/free/en/papers/zhao-2026-maestro-meta-learning-adaptive-estimation/)** *(2026 · 1 citation)* GRPO aligns LLMs well when answers can be checked automatically, as in math or code. Open-ended generation has no such check, and its goals often conflict, for example creativity versus factuality. Existing fixes either rely on costly LLM judges or combine cheap heuristic rewards (perplexity, entropy, format) using… 3. **[Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration](https://md.research.elamur.ai/free/en/papers/zhao-2026-consolidation-or-adaptation-prism-disentangling/)** *(2026)* The usual recipe for training LLM agents runs a supervised fine-tuning (SFT) stage first and a reinforcement learning (RL) stage after it. 4. **[Is EEG-to-Text Feasible in Real-World Scenarios? An In-Depth Analysis Using a Neuropsychology-Inspired Benchmark](https://md.research.elamur.ai/free/en/papers/zhang-2026-is-eeg-text-feasible-real/)** *(2026)* EEG-to-text (EEG2Text) decoding is a non-invasive alternative to implanted ECoG speech interfaces. However, most published systems only look competitive because they are scored with teacher-forcing. When models are not given the gold previous token, their output becomes meaningless, which has led researchers to doubt… 5. **[MDC-Bench: A Multidisciplinary Causal Benchmark Based on Causal Structures for Evaluating Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-mdc-bench-multidisciplinary-causal-benchmark/)** *(2026)* Most existing causal benchmarks for LLMs use everyday commonsense scenarios with short, single-hop cause–effect links. 6. **[PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data](https://md.research.elamur.ai/free/en/papers/xiong-2026-puzzleclone-dsl-powered-framework-synthesizing/)** *(2026)* Reasoning datasets with checkable answers are needed to train LLMs, but manually written puzzle collections are small. ## Co-authors here 12 of 19 co-authors with a page, the most papers together first. - [Xiao Ding](https://md.research.elamur.ai/free/en/authors/xiao-ding/) ×5 - [Bing Qin](https://md.research.elamur.ai/free/en/authors/bing-qin/) ×4 - [Ting Liu](https://md.research.elamur.ai/free/en/authors/ting-liu/) ×4 - [Bibo Cai](https://md.research.elamur.ai/free/en/authors/bibo-cai/) ×3 - [Hepeng Wang](https://md.research.elamur.ai/free/en/authors/hepeng-wang/) ×2 - [Jinglong Gao](https://md.research.elamur.ai/free/en/authors/jinglong-gao/) ×2 - [Li Du](https://md.research.elamur.ai/free/en/authors/li-du/) ×2 - [Yang Zhao](https://md.research.elamur.ai/free/en/authors/yang-zhao/) ×2 - [Yangou Ouyang](https://md.research.elamur.ai/free/en/authors/yangou-ouyang/) ×2 - [Zhouhao Sun](https://md.research.elamur.ai/free/en/authors/zhouhao-sun/) ×2 - [Chao Peng](https://md.research.elamur.ai/free/en/authors/chao-peng/) - [Dandan Tu](https://md.research.elamur.ai/free/en/authors/dandan-tu/) ## 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/) ×3: [ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/2026/) ×3 - [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/) ×2, [Findings of the Association for Computational Linguistics 2023](https://md.research.elamur.ai/free/en/venues/findings/2023/) ## Cited by Papers of our library cite their works 54 times (of the 149,439 papers whose bibliographies we read); [15 citing papers with a page here →](https://md.research.elamur.ai/free/en/authors/kai-xiong/cited-by/). Updated 2 November 2026