1 citations · 1 across the 10 of their papers we have counts for
12 papers
Which Coauthor Should I Nominate in My 99 ICLR Submissions? A Mathematical Analysis of the ICLR 2026 Reciprocal Reviewer Nomination Policy
Zhao Song, Song Yue, Jiahao Zhang
The rapid growth of AI conference submissions has created an overwhelming reviewing burden. To alleviate this, recent venues such as ICLR 2026 introduced a reviewer nomination poli…
Evaluating Frontier LLMs on PhD-Level Mathematical Reasoning: A Benchmark on a Textbook in Theoretical Computer Science about Randomized Algorithms
Yang Cao, Yubin Chen, Xuyang Guo +4
The rapid advancement of large language models (LLMs) has led to significant breakthroughs in automated mathematical reasoning and scientific discovery. Georgiev, Gmez-Serrano…
Fundamental Limits of Crystalline Equivariant Graph Neural Networks: A Circuit Complexity Perspective
Yang Cao, Zhao Song, Jiahao Zhang +1
Graph neural networks (GNNs) have become a core paradigm for learning on relational data. In materials science, equivariant GNNs (EGNNs) have emerged as a compelling backbone for c…
Your Vision-Language Model Can't Even Count to 20: Exposing the Failures of VLMs in Compositional Counting
Xuyang Guo, Zekai Huang, Zhenmei Shi +2
Vision-Language Models (VLMs) have become a central focus of today's AI community, owing to their impressive abilities gained from training on large-scale vision-language data from…
Too Easily Fooled? Prompt Injection Breaks LLMs on Frustratingly Simple Multiple-Choice Questions
Xuyang Guo, Zekai Huang, Zhao Song +1
Large Language Models (LLMs) have recently demonstrated strong emergent abilities in complex reasoning and zero-shot generalization, showing unprecedented potential for LLM-as-a-ju…
Towards High-Order Mean Flow Generative Models: Feasibility, Expressivity, and Provably Efficient Criteria
Yang Cao, Yubin Chen, Zhao Song +1
Generative modelling has seen significant advances through simulation-free paradigms such as Flow Matching, and in particular, the MeanFlow framework, which replaces instantaneous…
When a Paper Has 1000 Authors: Rethinking Citation Metrics in the Era of LLMs
Weihang Guo, Zhao Song, Jiahao Zhang
Author-level citation metrics provide a practical, interpretable, and scalable signal of scholarly influence in a complex research ecosystem. It has been widely used as a proxy in…
T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation
Yubin Chen, Xuyang Guo, Zhenmei Shi +2
Text-to-video (T2V) models have shown remarkable performance in generating visually reasonable scenes, while their capability to leverage world knowledge for ensuring semantic cons…
Thinking Isn't an Illusion: Overcoming the Limitations of Reasoning Models via Tool Augmentations
Zhao Song, Song Yue, Jiahao Zhang
Large Reasoning Models (LRMs) have become a central focus in today's large language model (LLM) research, where models are designed to output a step-by-step thinking process before…
Accept More, Reject Less: Reducing up to 19% Unnecessary Desk-Rejections over 11 Years of ICLR Data
Xiaoyu Li, Zhao Song, Jiahao Zhang
The explosive growth of AI research has driven paper submissions at flagship AI conferences to unprecedented levels, necessitating many venues in 2025 (e.g., CVPR, ICCV, KDD, AAAI,…
T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models
Xuyang Guo, Jiayan Huo, Zhenmei Shi +3
Thanks to recent advancements in scalable deep architectures and large-scale pretraining, text-to-video generation has achieved unprecedented capabilities in producing high-fidelit…
T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation
Xuyang Guo, Jiayan Huo, Zhenmei Shi +3
Text-to-video generative models have made significant strides in recent years, producing high-quality videos that excel in both aesthetic appeal and accurate instruction following,…