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From the 1 of 52 linked papers with an AI index.

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20242026
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cs.CL2026

VCG-Bench: Towards A Unified Visual-Centric Benchmark for Structured Generation and Editing

Xiaoyan Su, Peijie Dong, Zhenheng Tang +8

Despite the rapid advancements in Vision-Language Models (VLMs), a critical gap remains in their ability to handle structured, controllable diagrammatic tasks essential for profess…

cs.CL2026

Semantic Integrity Matters: Benchmarking and Preserving High-Density Reasoning in KV Cache Compression

Xiang Liu, Zhenheng Tang, Hong Chen +6

While Key-Value (KV) cache compression is essential for efficient LLM inference, current evaluations disproportionately focus on sparse retrieval tasks, potentially masking the deg…

cs.CL2026

DiffAdapt: Difficulty-Adaptive Reasoning for Token-Efficient LLM Inference

Xiang Liu, Xuming Hu, Xiaowen Chu +1

Recent reasoning Large Language Models (LLMs) demonstrate remarkable problem-solving abilities but often generate long thinking traces whose utility is unclear. Our work aims to im…

cs.CL2025

AnTKV: Anchor Token-Aware Sub-Bit Vector Quantization for KV Cache in Large Language Models

Zeyu Li, Chuanfu Xiao, Yang Wang +6

Quantization has emerged as an effective and lightweight solution to reduce the memory footprint of the KV cache in Large Language Models. Nevertheless, minimizing the accuracy deg…

cs.CL2025

ChunkKV: Semantic-Preserving KV Cache Compression for Efficient Long-Context LLM Inference

Xiang Liu, Zhenheng Tang, Peijie Dong +5

Large Language Models (LLMs) require significant GPU memory when processing long texts, with the key value (KV) cache consuming up to 70\% of total memory during inference. Althoug…

cs.CL2025

FlowKV: Enhancing Multi-Turn Conversational Coherence in LLMs via Isolated Key-Value Cache Management

Xiang Liu, Hong Chen, Xuming Hu +1

Large Language Models (LLMs) are increasingly deployed in multi-turn conversational applications, where the management of the Key-Value (KV) Cache presents a significant bottleneck…