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cs.IR2026
GACC-Bench: Benchmarking Goal-Adaptive Context Compression Ability across Large Language Models
Weiting Liu, Zhiyu Pan, Shuhong Wang +7
Context compression in long-running applications of large language models (LLMs) must preserve goal-relevant information, often before specific downstream questions are known. We i…
cs.RO2026
EdgeNav-QE: QLoRA Quantization and Dynamic Early Exit for LAM-based Navigation on Edge Devices
Mengyun Liu, Shanshan Huang, Jianan Jiang
Large Action Models (LAMs) have shown immense potential in autonomous navigation by bridging high-level reasoning with low-level control. However, deploying these multi-billion par…
cs.CL2026
HeteroCache: A Dynamic Retrieval Approach to Heterogeneous KV Cache Compression for Long-Context LLM Inference
Zhiyuan Shi, Qibo Qiu, Feng Xue +5
The linear memory growth of the KV cache poses a significant bottleneck for LLM inference in long-context tasks. Existing static compression methods often fail to preserve globally…