Search Results for author: Sheng Bi

Found 11 papers, 2 papers with code

TEII: Think, Explain, Interact and Iterate with Large Language Models to Solve Cross-lingual Emotion Detection

no code implementations27 May 2024 Long Cheng, Qihao Shao, Christine Zhao, Sheng Bi, Gina-Anne Levow

Cross-lingual emotion detection allows us to analyze global trends, public opinion, and social phenomena at scale.

Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models

no code implementations21 May 2024 Jiaqi Li, Qianshan Wei, Chuanyi Zhang, Guilin Qi, Miaozeng Du, Yongrui Chen, Sheng Bi

Alongside our method, we establish MMUBench, a new benchmark for MU in MLLMs and introduce a collection of metrics for its evaluation.

Machine Unlearning

Benchmarking Large Language Models in Complex Question Answering Attribution using Knowledge Graphs

no code implementations26 Jan 2024 Nan Hu, Jiaoyan Chen, Yike Wu, Guilin Qi, Sheng Bi, Tongtong Wu, Jeff Z. Pan

The attribution of question answering is to provide citations for supporting generated statements, and has attracted wide research attention.

Benchmarking Knowledge Graphs +1

Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering

1 code implementation20 Sep 2023 Yike Wu, Nan Hu, Sheng Bi, Guilin Qi, Jie Ren, Anhuan Xie, Wei Song

To this end, we propose an answer-sensitive KG-to-Text approach that can transform KG knowledge into well-textualized statements most informative for KGQA.

Graph Question Answering Language Modelling +2

Ion Clusters and Networks in "Water-in-Salt Electrolytes"

no code implementations8 Mar 2021 Michael McEldrew, Zachary A. H. Goodwin, Sheng Bi, Alexei A. Kornyshev, Martin Z. Bazant

Our model is able to quantitatively reproduce the populations of ionic clusters of different sizes as a function of salt concentration, the critical salt concentration for ionic gelation, and the fraction of ions incorporated into the ionic gel, as observed from molecular simulations of three different lithium-based WiSEs.

Chemical Physics Soft Condensed Matter Statistical Mechanics

Knowledge-enriched, Type-constrained and Grammar-guided Question Generation over Knowledge Bases

no code implementations COLING 2020 Sheng Bi, Xiya Cheng, Yuan-Fang Li, Yongzhen Wang, Guilin Qi

Question generation over knowledge bases (KBQG) aims at generating natural-language questions about a subgraph, i. e. a set of (connected) triples.

Decoder Question Generation +1

Knowledge-aware Method for Confusing Charge Prediction

no code implementations7 Oct 2020 Xiya Cheng, Sheng Bi, Guilin Qi, Yongzhen Wang

In this paper, we propose a knowledge-attentive neural network model, which introduces legal schematic knowledge about charges and exploit the knowledge hierarchical representation as the discriminative features to differentiate confusing charges.

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