5 papers
CHAIN: Calibrated LLM Forecasting via Causal-Temporal Hypergraph Inference
Wenjin Liu, Chenxi Wang, Yue Lu +2
Large language models have achieved significant progress in event forecasting, yet their probability outputs exhibit systematic calibration bias that varies heterogeneously across…
AdaPilot: Towards Scene-Adaptive Policy Learning for Cross-Generator Text-to-Image Quality Optimization
Wenjin Liu, Fayuan Ke, Yue Lu +3
Existing methods for improving text-to-image generation quality have progressed from generator fine-tuning and prompt optimization to reinforcement learning with multi-turn visual…
MMDynOpt-Agent: Dynamic Optimization for Multimodal Large Language Model Reasoning via Reinforcement Learning
Wenjin Liu, Haoran Luo, Fayuan Ke +5
Recently, multimodal large language models (MLLMs) have demonstrated strong potential in visual understanding and complex reasoning tasks. However, existing methods often struggle…
Web-CogReasoner: Towards Multimodal Knowledge-Induced Cognitive Reasoning for Web Agents
Yuhan Guo, Cong Guo, Aiwen Sun +12
Multimodal large-scale models have significantly advanced the development of web agents, enabling perception and interaction with digital environments akin to human cognition. In t…
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision
Che Liu, Yingji Zhang, Dong Zhang +13
This work proposes an industry-level omni-modal large language model (LLM) pipeline that integrates auditory, visual, and linguistic modalities to overcome challenges such as limit…