activity
20242026
most citedDeepSeek-V3 Technical Report

268 citations · 272 across the 13 of their papers we have counts for

collaborators

23 papers

cs.CV2026

VideoZeroBench: Probing the Limits of Video MLLMs with Spatio-Temporal Evidence Verification

Jiahao Meng, Tan Yue, Qi Xu +7

Recent video multimodal large language models achieve impressive results across various benchmarks. However, current evaluations suffer from two critical limitations: (1) inflated…

cs.CL2026

Gender Bias in MT for a Genderless Language: New Benchmarks for Basque

Amaia Murillo, Olatz-Perez-de-Viñaspre, Naiara Perez

Large language models (LLMs) and machine translation (MT) systems are increasingly used in our daily lives, but their outputs can reproduce gender bias present in the training data…

cs.CL2026

MMFormalizer: Multimodal Autoformalization in the Wild

Jing Xiong, Qi Han, Yunta Hsieh +11

Autoformalization, which translates natural language mathematics into formal statements to enable machine reasoning, faces fundamental challenges in the wild due to the multimodal…

cs.AI2025

Cognitive Foundations for Reasoning and Their Manifestation in LLMs

Priyanka Kargupta, Shuyue Stella Li, Haocheng Wang +9

Large language models (LLMs) solve complex problems yet fail on simpler variants, suggesting they achieve correct outputs through mechanisms fundamentally different from human reas…

cs.CV2025

MMaDA-Parallel: Multimodal Large Diffusion Language Models for Thinking-Aware Editing and Generation

Ye Tian, Ling Yang, Jiongfan Yang +10

While thinking-aware generation aims to improve performance on complex tasks, we identify a critical failure mode where existing sequential, autoregressive approaches can paradoxic…

cs.CV2025

MVU-Eval: Towards Multi-Video Understanding Evaluation for Multimodal LLMs

Tianhao Peng, Haochen Wang, Yuanxing Zhang +13

The advent of Multimodal Large Language Models (MLLMs) has expanded AI capabilities to visual modalities, yet existing evaluation benchmarks remain limited to single-video understa…