9 citations · 14 across the 12 of their papers we have counts for
6 papers · 1 filter
Abstraction-of-Thought Makes Language Models Better Reasoners
Ruixin Hong, Hongming Zhang, Xiaoman Pan +2
Abstract reasoning, the ability to reason from the abstract essence of a problem, serves as a key to generalization in human reasoning. However, eliciting language models to perfor…
Fact-and-Reflection (FaR) Improves Confidence Calibration of Large Language Models
Xinran Zhao, Hongming Zhang, Xiaoman Pan +4
For a LLM to be trustworthy, its confidence level should be well-calibrated with its actual performance. While it is now common sense that LLM performances are greatly impacted by…
Zebra: Extending Context Window with Layerwise Grouped Local-Global Attention
Kaiqiang Song, Xiaoyang Wang, Sangwoo Cho +2
This paper introduces a novel approach to enhance the capabilities of Large Language Models (LLMs) in processing and understanding extensive text sequences, a critical aspect in ap…
Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
Wenhao Yu, Hongming Zhang, Xiaoman Pan +3
Retrieval-augmented language models (RALMs) represent a substantial advancement in the capabilities of large language models, notably in reducing factual hallucination by leveragin…
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning
Xuansheng Wu, Wenlin Yao, Jianshu Chen +4
Large Language Models (LLMs) have achieved remarkable success, where instruction tuning is the critical step in aligning LLMs with user intentions. In this work, we investigate how…
LASER: LLM Agent with State-Space Exploration for Web Navigation
Kaixin Ma, Hongming Zhang, Hongwei Wang +3
Large language models (LLMs) have been successfully adapted for interactive decision-making tasks like web navigation. While achieving decent performance, previous methods implicit…