15 papers
Online Dynamic Batching with Formal Guarantees for LLM Training
Dian Li, Zekun Wang, Yaoru Wang +1
Modern LLM training breaks a core assumption behind offline batch samplers: the true training cost of a sample is only observable after preprocessing, augmentation, templating, tok…
Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion
Yexing Du, Youcheng Pan, Zekun Wang +7
Multimodal Large Language Models (MLLMs) have achieved notable success in enhancing translation performance by integrating multimodal information. However, existing research primar…
Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models
Runxuan Liu, Xianhao Ou, Xinyan Ma +13
Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Mode…
AI Meets Brain: Memory Systems from Cognitive Neuroscience to Autonomous Agents
Jiafeng Liang, Hao Li, Chang Li +12
Memory serves as the pivotal nexus bridging past and future, providing both humans and AI systems with invaluable concepts and experience to navigate complex tasks. Recent research…
Scaling Computer-Use Grounding via User Interface Decomposition and Synthesis
Tianbao Xie, Jiaqi Deng, Xiaochuan Li +12
Graphical user interface (GUI) grounding, the ability to map natural language instructions to specific actions on graphical user interfaces, remains a critical bottleneck in comput…
EffiVLM-BENCH: A Comprehensive Benchmark for Evaluating Training-Free Acceleration in Large Vision-Language Models
Zekun Wang, Minghua Ma, Zexin Wang +4
Large Vision-Language Models (LVLMs) have achieved remarkable success, yet their significant computational demands hinder practical deployment. While efforts to improve LVLM effici…