3 papers
cs.CV2026
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…
cs.CV2025
Not All Attention Heads Are What You Need: Refining CLIP's Image Representation with Attention Ablation
Feng Lin, Marco Chen, Haokui Zhang +3
This paper investigates the role of attention heads in CLIP's image encoder. Building on interpretability studies, we conduct an exhaustive analysis and find that certain heads, di…
cs.CL2025
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…