1 citations · 1 across the 5 of their papers we have counts for
5 papers
LookaheadKV: Fast and Accurate KV Cache Eviction by Glimpsing into the Future without Generation
Jinwoo Ahn, Ingyu Seong, Akhil Kedia +4
Transformer-based large language models (LLMs) rely on key-value (KV) caching to avoid redundant computation during autoregressive inference. While this mechanism greatly improves…
Sparse Logit Sampling: Accelerating Knowledge Distillation in LLMs
Anshumann, Mohd Abbas Zaidi, Akhil Kedia +5
Knowledge distillation can be a cost-effective technique to distill knowledge in Large Language Models, if the teacher output logits can be pre-computed and cached. However, succes…
Fine-Grained Open-Vocabulary Object Recognition via User-Guided Segmentation
Jinwoo Ahn, Hyeokjoon Kwon, Hwiyeon Yoo
Recent advent of vision-based foundation models has enabled efficient and high-quality object detection at ease. Despite the success of previous studies, object detection models fa…
VAGUE: Visual Contexts Clarify Ambiguous Expressions
Heejeong Nam, Jinwoo Ahn, Keummin Ka +2
Human communication often relies on visual cues to resolve ambiguity. While humans can intuitively integrate these cues, AI systems often find it challenging to engage in sophistic…
Recursive Chain-of-Feedback Prevents Performance Degradation from Redundant Prompting
Jinwoo Ahn, Kyuseung Shin
Large Language Models (LLMs) frequently struggle with complex reasoning tasks, failing to construct logically sound steps towards the solution. In response to this behavior, users…