1 citations · 2 across the 5 of their papers we have counts for
5 papers
DivScene: Towards Open-Vocabulary Object Navigation with Large Vision Language Models in Diverse Scenes
Zhaowei Wang, Hongming Zhang, Tianqing Fang +6
Large Vision-Language Models (LVLMs) have achieved significant progress in tasks like visual question answering and document understanding. However, their potential to comprehend e…
NegotiationToM: A Benchmark for Stress-testing Machine Theory of Mind on Negotiation Surrounding
Chunkit Chan, Cheng Jiayang, Yauwai Yim +7
Large Language Models (LLMs) have sparked substantial interest and debate concerning their potential emergence of Theory of Mind (ToM) ability. Theory of mind evaluations currently…
AbsInstruct: Eliciting Abstraction Ability from LLMs through Explanation Tuning with Plausibility Estimation
Zhaowei Wang, Wei Fan, Qing Zong +7
Abstraction ability is crucial in human intelligence, which can also benefit various tasks in NLP study. Existing work shows that LLMs are deficient in abstract ability, and how to…
AbsPyramid: Benchmarking the Abstraction Ability of Language Models with a Unified Entailment Graph
Zhaowei Wang, Haochen Shi, Weiqi Wang +5
Cognitive research indicates that abstraction ability is essential in human intelligence, which remains under-explored in language models. In this paper, we present AbsPyramid, a u…
StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding
Cheng Jiayang, Lin Qiu, Tsz Ho Chan +9
Analogy-making between narratives is crucial for human reasoning. In this paper, we evaluate the ability to identify and generate analogies by constructing a first-of-its-kind larg…