6 papers
From Agents to Edges: Paired Optimization for Multi-Agent Collaboration
Feng Lin, Xiaotian Yu, Yifan Yang +1
Strong individual agents do not guarantee effective collaboration. Communication must align what one agent conveys with how another interprets and uses it. This dependency makes th…
Bridging Coarse and Fine Recognition: A Hybrid Approach for Open-Ended Multi-Granularity Object Recognition in Interactive Educational Games
Hanling Yi, Feng Lin, Mao Luo +3
Recent advances in Multimodal Large Language Models (MLLMs) have enabled open-ended object recognition, yet they struggle with fine-grained tasks. In contrast, CLIP-style models ex…
EvoTok: A Unified Image Tokenizer via Residual Latent Evolution for Visual Understanding and Generation
Yan Li, Ning Liao, Xiangyu Zhao +5
The development of unified multimodal large language models (MLLMs) is fundamentally challenged by the granularity gap between visual understanding and generation: understanding re…
HCAttention: Extreme KV Cache Compression via Heterogeneous Attention Computing for LLMs
Dongquan Yang, Yifan Yang, Xiaotian Yu +2
Processing long-context inputs with large language models presents a significant challenge due to the enormous memory requirements of the Key-Value (KV) cache during inference. Exi…
OS-W2S: An Automatic Labeling Engine for Language-Guided Open-Set Aerial Object Detection
Guoting Wei, Yu Liu, Xia Yuan +7
In recent years, language-guided open-set aerial object detection has gained significant attention due to its better alignment with real-world application needs. However, due to li…
BiTA: Bi-Directional Tuning for Lossless Acceleration in Large Language Models
Feng Lin, Hanling Yi, Hongbin Li +4
Large language models (LLMs) commonly employ autoregressive generation during inference, leading to high memory bandwidth demand and consequently extended latency. To mitigate this…