3 papers
cs.LG2026
HARD-KV: Head-Adaptive Regularization for Decoding-time KV Compression
Yuxuan Yang, Feiyang Ren, Bowen Zeng +4
Long-context LLM inference faces a fundamental conflict: head-adaptive compression algorithms (e.g., Top- nucleus sampling) offer superior accuracy by dynamically fluctuating me…
cs.CL2026
Efficient Inference for Large Vision-Language Models: Bottlenecks, Techniques, and Prospects
Jun Zhang, Yicheng Ji, Feiyang Ren +7
Large Vision-Language Models (LVLMs) enable sophisticated reasoning over images and videos, yet their inference is hindered by a systemic efficiency barrier known as visual token d…
cs.AI2026
HybridKV: Hybrid KV Cache Compression for Efficient Multimodal Large Language Model Inference
Bowen Zeng, Feiyang Ren, Jun Zhang +4
Multimodal Large Language Models (MLLMs) have advanced unified reasoning over text, images, and videos, but their inference is hindered by the rapid growth of key-value (KV) caches…