Search Results for author:
Found 5 papers, 2 papers with code
An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation
Retrieval-augmented generation integrates the capabilities of large language models with relevant information retrieved from an extensive corpus, yet encounters challenges when confronted with real-world noisy data.
Divide-and-Conquer Meets Consensus: Unleashing the Power of Functions in Code Generation
To this end, we propose FunCoder, a code generation framework incorporating the divide-and-conquer strategy with functional consensus.
TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models
Understanding time is a pivotal aspect of human cognition, crucial in the broader framework of grasping the intricacies of the world.
Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future
We hope this paper serves as an introduction for beginners and fosters future research.
SmartTrim: Adaptive Tokens and Attention Pruning for Efficient Vision-Language Models
Despite achieving remarkable performance on various vision-language tasks, Transformer-based Vision-Language Models (VLMs) suffer from redundancy in inputs and parameters, significantly hampering their efficiency in real-world applications.
