activity
20162024
most citedOptimal scheduling of park-level integrated energy system considering ladder-type carbon trading mechanism and flexible load

76 citations · 182 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CL20241 cited

Mitigating Social Biases in Language Models through Unlearning

Omkar Dige, Diljot Singh, Tsz Fung Yau +4

Mitigating bias in language models (LMs) has become a critical problem due to the widespread deployment of LMs. Numerous approaches revolve around data pre-processing and fine-tuni…

cs.CL2024

DARA: Decomposition-Alignment-Reasoning Autonomous Language Agent for Question Answering over Knowledge Graphs

Haishuo Fang, Xiaodan Zhu, Iryna Gurevych

Answering Questions over Knowledge Graphs (KGQA) is key to well-functioning autonomous language agents in various real-life applications. To improve the neural-symbolic reasoning c…

cs.CL2024

SpaRC and SpaRP: Spatial Reasoning Characterization and Path Generation for Understanding Spatial Reasoning Capability of Large Language Models

Md Imbesat Hassan Rizvi, Xiaodan Zhu, Iryna Gurevych

Spatial reasoning is a crucial component of both biological and artificial intelligence. In this work, we present a comprehensive study of the capability of current state-of-the-ar…

cs.AI20241 cited

Evaluating AI for Law: Bridging the Gap with Open-Source Solutions

Rohan Bhambhoria, Samuel Dahan, Jonathan Li +1

This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It s…

cs.CL2024

Self-Consistent Decoding for More Factual Open Responses

Christopher Malon, Xiaodan Zhu

Self-consistency has emerged as a powerful method for improving the accuracy of short answers generated by large language models. As previously defined, it only concerns the accura…

cs.LG20231 cited

Parameter-Efficient Methods for Metastases Detection from Clinical Notes

Maede Ashofteh Barabadi, Xiaodan Zhu, Wai Yip Chan +2

Understanding the progression of cancer is crucial for defining treatments for patients. The objective of this study is to automate the detection of metastatic liver disease from f…