20 papers
Reference-Free Post-Training of Open Large Language Models for Multilingual Machine Translation
Chris Han, Pengzhi Gao, Pei Fu +1
We study reference-free post-training for multilingual machine translation with open large language models. Starting from the supervised-finetuned MiLMMT-46-v0.1 models, we apply G…
Switch-Reasoner: Learn When to Think in Multitask Mixtures via Reinforcement Learning
Yiyang Fang, Pei Fu, Jinjie Li +7
Multimodal Large Language Models (MLLMs) often follow a fixed Think-then-Answer paradigm, which is inefficient in heterogeneous multitask settings because simple inputs may not req…
DeltaV: Thinking with Visual State Updates in Unified Large Multimodal Models
Pengjie Wang, Linger Deng, Zujia Zhang +6
Current Unified Large Multimodal Models (ULMMs) support interleaved multimodal reasoning through textual reasoning and intermediate visual states, but typically generate each visua…
EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models
Yiyang Fang, Wenke Huang, Pei Fu +5
Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual reasoning and understanding tasks but still struggle to capture the complexity and subjectivity of…
UI-MOPD: Multi-Platform On-Policy Distillation for Unified GUI Agents
Niu Lian, Tongbo Chen, Alan Chen +10
Recent advances in multimodal foundation models and agent systems have driven GUI agents from single-platform task execution toward cross-platform interaction. However, unified mul…
ELVA: Exploring Ranking-Driven Universal Multimodal Retrieval
Yuhan Liu, Pei Fu, Hang Li +8
Leveraging Multimodal Large Language Models (MLLMs) via contrastive learning has become a mainstream paradigm for improving the performance of Universal Multimodal Retrieval (UMR).…