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cs.CL2025

Uni-MoE-2.0-Omni: Scaling Language-Centric Omnimodal Large Model with Advanced MoE, Training and Data

Yunxin Li, Xinyu Chen, Shenyuan Jiang +9

We present Uni-MoE 2.0 from the Lychee family. As a fully open-source omnimodal large model (OLM), it substantially advances Lychee's Uni-MoE series in language-centric multimodal…

cs.CL2025

AnTKV: Anchor Token-Aware Sub-Bit Vector Quantization for KV Cache in Large Language Models

Zeyu Li, Chuanfu Xiao, Yang Wang +6

Quantization has emerged as an effective and lightweight solution to reduce the memory footprint of the KV cache in Large Language Models. Nevertheless, minimizing the accuracy deg…

cs.CL2025

VerIPO: Cultivating Long Reasoning in Video-LLMs via Verifier-Gudied Iterative Policy Optimization

Yunxin Li, Xinyu Chen, Zitao Li +5

Applying Reinforcement Learning (RL) to Video Large Language Models (Video-LLMs) shows significant promise for complex video reasoning. However, popular Reinforcement Fine-Tuning (…

cs.CL2024

LLMs Meet Long Video: Advancing Long Video Question Answering with An Interactive Visual Adapter in LLMs

Yunxin Li, Xinyu Chen, Baotain Hu +1

Long video understanding is a significant and ongoing challenge in the intersection of multimedia and artificial intelligence. Employing large language models (LLMs) for comprehend…

cs.CL2024

A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question Answering

Yunxin Li, Longyue Wang, Baotian Hu +5

The emergence of multimodal large models (MLMs) has significantly advanced the field of visual understanding, offering remarkable capabilities in the realm of visual question answe…

cs.CL2024

Cognitive Visual-Language Mapper: Advancing Multimodal Comprehension with Enhanced Visual Knowledge Alignment

Yunxin Li, Xinyu Chen, Baotian Hu +2

Evaluating and Rethinking the current landscape of Large Multimodal Models (LMMs), we observe that widely-used visual-language projection approaches (e.g., Q-former or MLP) focus o…