Search Results for author: Aiwei Liu

Found 19 papers, 9 papers with code

An Entropy-based Text Watermarking Detection Method

no code implementations20 Mar 2024 Yijian Lu, Aiwei Liu, Dianzhi Yu, Jingjing Li, Irwin King

In this work, we proposed that the influence of token entropy should be fully considered in the watermark detection process, that is, the weight of each token should be adjusted according to its entropy during watermark detection, rather than setting the weight of all tokens to the same value as in previous methods.

ChatCite: LLM Agent with Human Workflow Guidance for Comparative Literature Summary

no code implementations5 Mar 2024 Yutong Li, Lu Chen, Aiwei Liu, Kai Yu, Lijie Wen

In this work, we firstly focus on the independent literature summarization step and introduce ChatCite, an LLM agent with human workflow guidance for comparative literature summary.

Retrieval

Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models

no code implementations21 Feb 2024 Zhiwei He, Binglin Zhou, Hongkun Hao, Aiwei Liu, Xing Wang, Zhaopeng Tu, Zhuosheng Zhang, Rui Wang

Furthermore, we analyze two key factors that contribute to the cross-lingual consistency in text watermarking and propose a defense method that increases the AUC from 0. 67 to 0. 88 under CWRA.

TAG

Direct Large Language Model Alignment Through Self-Rewarding Contrastive Prompt Distillation

no code implementations19 Feb 2024 Aiwei Liu, Haoping Bai, Zhiyun Lu, Xiang Kong, Simon Wang, Jiulong Shan, Meng Cao, Lijie Wen

In this paper, we propose a method to evaluate the response preference by using the output probabilities of response pairs under contrastive prompt pairs, which could achieve better performance on LLaMA2-7B and LLaMA2-13B compared to RLAIF.

Language Modelling Large Language Model

A Survey of Text Watermarking in the Era of Large Language Models

no code implementations13 Dec 2023 Aiwei Liu, Leyi Pan, Yijian Lu, Jingjing Li, Xuming Hu, Xi Zhang, Lijie Wen, Irwin King, Hui Xiong, Philip S. Yu

Text watermarking algorithms play a crucial role in the copyright protection of textual content, yet their capabilities and application scenarios have been limited historically.

Dialogue Generation

Prompt Me Up: Unleashing the Power of Alignments for Multimodal Entity and Relation Extraction

1 code implementation25 Oct 2023 Xuming Hu, Junzhe Chen, Aiwei Liu, Shiao Meng, Lijie Wen, Philip S. Yu

Additionally, our method is orthogonal to previous multimodal fusions, and using it on prior SOTA fusions further improves 5. 47% F1.

Relation Relation Extraction

RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation Extraction

1 code implementation24 Oct 2023 Shiao Meng, Xuming Hu, Aiwei Liu, Shu'ang Li, Fukun Ma, Yawen Yang, Lijie Wen

However, existing works often struggle to obtain class prototypes with accurate relational semantics: 1) To build prototype for a target relation type, they aggregate the representations of all entity pairs holding that relation, while these entity pairs may also hold other relations, thus disturbing the prototype.

Document-level Relation Extraction Meta-Learning +1

A Semantic Invariant Robust Watermark for Large Language Models

1 code implementation10 Oct 2023 Aiwei Liu, Leyi Pan, Xuming Hu, Shiao Meng, Lijie Wen

In this work, we propose a semantic invariant watermarking method for LLMs that provides both attack robustness and security robustness.

An Unforgeable Publicly Verifiable Watermark for Large Language Models

2 code implementations30 Jul 2023 Aiwei Liu, Leyi Pan, Xuming Hu, Shu'ang Li, Lijie Wen, Irwin King, Philip S. Yu

Experiments demonstrate that our algorithm attains high detection accuracy and computational efficiency through neural networks with a minimized number of parameters.

Computational Efficiency

Exploring the Compositional Generalization in Context Dependent Text-to-SQL Parsing

no code implementations29 May 2023 Aiwei Liu, Wei Liu, Xuming Hu, Shuang Li, Fukun Ma, Yawen Yang, Lijie Wen

Based on these observations, we propose a method named \texttt{p-align} to improve the compositional generalization of Text-to-SQL models.

SQL Parsing Text-To-SQL

GDA: Generative Data Augmentation Techniques for Relation Extraction Tasks

no code implementations26 May 2023 Xuming Hu, Aiwei Liu, Zeqi Tan, Xin Zhang, Chenwei Zhang, Irwin King, Philip S. Yu

These techniques neither preserve the semantic consistency of the original sentences when rule-based augmentations are adopted, nor preserve the syntax structure of sentences when expressing relations using seq2seq models, resulting in less diverse augmentations.

Data Augmentation Relation +1

Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks

no code implementations19 Oct 2022 Xuming Hu, Yong Jiang, Aiwei Liu, Zhongqiang Huang, Pengjun Xie, Fei Huang, Lijie Wen, Philip S. Yu

Data augmentation techniques have been used to alleviate the problem of scarce labeled data in various NER tasks (flat, nested, and discontinuous NER tasks).

Data Augmentation named-entity-recognition +3

Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graph

1 code implementation8 Aug 2022 Aiwei Liu, Xuming Hu, Li Lin, Lijie Wen

First, we extract a schema linking graph from PLMs through a probing procedure in an unsupervised manner.

Graph Learning SQL Parsing +1

A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference

no code implementations31 May 2022 Shu'ang Li, Xuming Hu, Li Lin, Aiwei Liu, Lijie Wen, Philip S. Yu

Natural Language Inference (NLI) is a growingly essential task in natural language understanding, which requires inferring the relationship between the sentence pairs (premise and hypothesis).

Contrastive Learning Data Augmentation +5

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