15 papers
Ares: Adaptive Reasoning Effort Selection for Efficient LLM Agents
Jingbo Yang, Bairu Hou, Wei Wei +2
Modern agents powered by thinking LLMs achieve high accuracy through long chain-of-thought reasoning but incur substantial inference costs. While many LLMs now support configurable…
Adaptive Data Augmentation with Multi-armed Bandit: Sample-Efficient Embedding Calibration for Implicit Pattern Recognition
Minxue Tang, Yangyang Yu, Aolin Ding +3
Recognizing implicit visual and textual patterns is essential in many real-world applications of modern AI. However, tackling long-tail pattern recognition tasks remains challengin…
Observations and Remedies for Large Language Model Bias in Self-Consuming Performative Loop
Yaxuan Wang, Zhongteng Cai, Yujia Bao +2
The rapid advancement of large language models (LLMs) has led to growing interest in using synthetic data to train future models. However, this creates a self-consuming retraining…
PromptBridge: Cross-Model Prompt Transfer for Large Language Models
Yaxuan Wang, Quan Liu, Zhenting Wang +4
Large language models (LLMs) underpin applications in code generation, mathematical reasoning, and agent-based workflows. In practice, systems access LLMs via commercial APIs or op…
DRAGON: Guard LLM Unlearning in Context via Negative Detection and Reasoning
Yaxuan Wang, Chris Yuhao Liu, Quan Liu +4
Unlearning in Large Language Models (LLMs) is crucial for protecting private data and removing harmful knowledge. Most existing approaches rely on fine-tuning to balance unlearning…
KVLink: Accelerating Large Language Models via Efficient KV Cache Reuse
Jingbo Yang, Bairu Hou, Wei Wei +2
We describe KVLink, an approach for efficient key-value (KV) cache reuse in large language models (LLMs). In many LLM applications, different inputs can share overlapping context,…