Search Results for author: Jifan Yu

Found 36 papers, 23 papers with code

HOSMEL: A Hot-Swappable Modularized Entity Linking Toolkit for Chinese

1 code implementation ACL 2022 Daniel Zhang-li, Jing Zhang, Jifan Yu, Xiaokang Zhang, Peng Zhang, Jie Tang, Juanzi Li

We investigate the usage of entity linking (EL)in downstream tasks and present the first modularized EL toolkit for easy task adaptation.

Entity Linking Question Answering

Transferable and Efficient Non-Factual Content Detection via Probe Training with Offline Consistency Checking

2 code implementations10 Apr 2024 Xiaokang Zhang, Zijun Yao, Jing Zhang, Kaifeng Yun, Jifan Yu, Juanzi Li, Jie Tang

Detecting non-factual content is a longstanding goal to increase the trustworthiness of large language models (LLMs) generations.

Question Answering

Evaluating Generative Language Models in Information Extraction as Subjective Question Correction

1 code implementation4 Apr 2024 Yuchen Fan, Yantao Liu, Zijun Yao, Jifan Yu, Lei Hou, Juanzi Li

(1) The imprecision of existing evaluation metrics that struggle to effectively gauge semantic consistency between model outputs and ground truth, and (2) The inherent incompleteness of evaluation benchmarks, primarily due to restrictive human annotation schemas, resulting in underestimated LLM performances.

Event Extraction Natural Language Inference +1

Untangle the KNOT: Interweaving Conflicting Knowledge and Reasoning Skills in Large Language Models

1 code implementation4 Apr 2024 Yantao Liu, Zijun Yao, Xin Lv, Yuchen Fan, Shulin Cao, Jifan Yu, Lei Hou, Juanzi Li

However, knowledge in the document may conflict with the memory of LLMs due to outdated or incorrect knowledge in the LLMs' parameters.

Question Answering

A Cause-Effect Look at Alleviating Hallucination of Knowledge-grounded Dialogue Generation

no code implementations4 Apr 2024 Jifan Yu, Xiaohan Zhang, Yifan Xu, Xuanyu Lei, Zijun Yao, Jing Zhang, Lei Hou, Juanzi Li

Recently, knowledge-grounded dialogue generation models, that intentionally invoke external knowledge resources to more informative responses, are also proven to be effective in reducing hallucination.

counterfactual Counterfactual Reasoning +2

TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios

1 code implementation28 Mar 2024 Xiaokang Zhang, Jing Zhang, Zeyao Ma, Yang Li, Bohan Zhang, Guanlin Li, Zijun Yao, Kangli Xu, Jinchang Zhou, Daniel Zhang-li, Jifan Yu, Shu Zhao, Juanzi Li, Jie Tang

We introduce TableLLM, a robust large language model (LLM) with 13 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embedded within documents or spreadsheets, catering to real-world office scenarios.

Language Modelling Large Language Model

Reverse That Number! Decoding Order Matters in Arithmetic Learning

no code implementations9 Mar 2024 Daniel Zhang-li, Nianyi Lin, Jifan Yu, Zheyuan Zhang, Zijun Yao, Xiaokang Zhang, Lei Hou, Jing Zhang, Juanzi Li

Recent advancements in pretraining have demonstrated that modern Large Language Models (LLMs) possess the capability to effectively learn arithmetic operations.

PST-Bench: Tracing and Benchmarking the Source of Publications

1 code implementation25 Feb 2024 Fanjin Zhang, Kun Cao, Yukuo Cen, Jifan Yu, Da Yin, Jie Tang

Tracing the source of research papers is a fundamental yet challenging task for researchers.


OAG-Bench: A Human-Curated Benchmark for Academic Graph Mining

no code implementations24 Feb 2024 Fanjin Zhang, Shijie Shi, Yifan Zhu, Bo Chen, Yukuo Cen, Jifan Yu, Yelin Chen, Lulu Wang, Qingfei Zhao, Yuqing Cheng, Tianyi Han, Yuwei An, Dan Zhang, Weng Lam Tam, Kun Cao, Yunhe Pang, Xinyu Guan, Huihui Yuan, Jian Song, Xiaoyan Li, Yuxiao Dong, Jie Tang

We envisage that OAG-Bench can serve as a common ground for the community to evaluate and compare algorithms in academic graph mining, thereby accelerating algorithm development and advancement in this field.

Graph Mining

WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models

1 code implementation13 Nov 2023 Shangqing Tu, Yuliang Sun, Yushi Bai, Jifan Yu, Lei Hou, Juanzi Li

To mitigate the potential misuse of large language models (LLMs), recent research has developed watermarking algorithms, which restrict the generation process to leave an invisible trace for watermark detection.

Benchmarking Instruction Following

VidCoM: Fast Video Comprehension through Large Language Models with Multimodal Tools

no code implementations16 Oct 2023 Ji Qi, Kaixuan Ji, Jifan Yu, Duokang Wang, Bin Xu, Lei Hou, Juanzi Li

Building models that comprehends videos and responds specific user instructions is a practical and challenging topic, as it requires mastery of both vision understanding and knowledge reasoning.

Caption Generation Descriptive +3

Mastering the Task of Open Information Extraction with Large Language Models and Consistent Reasoning Environment

no code implementations16 Oct 2023 Ji Qi, Kaixuan Ji, Xiaozhi Wang, Jifan Yu, Kaisheng Zeng, Lei Hou, Juanzi Li, Bin Xu

Open Information Extraction (OIE) aims to extract objective structured knowledge from natural texts, which has attracted growing attention to build dedicated models with human experience.

In-Context Learning Open Information Extraction

Exploring the Cognitive Knowledge Structure of Large Language Models: An Educational Diagnostic Assessment Approach

no code implementations12 Oct 2023 Zheyuan Zhang, Jifan Yu, Juanzi Li, Lei Hou

We aim to reveal the knowledge structures of LLMs and gain insights of their cognitive capabilities.

LittleMu: Deploying an Online Virtual Teaching Assistant via Heterogeneous Sources Integration and Chain of Teach Prompts

1 code implementation11 Aug 2023 Shangqing Tu, Zheyuan Zhang, Jifan Yu, Chunyang Li, Siyu Zhang, Zijun Yao, Lei Hou, Juanzi Li

However, few MOOC platforms are providing human or virtual teaching assistants to support learning for massive online students due to the complexity of real-world online education scenarios and the lack of training data.

Language Modelling Question Answering +1

VisKoP: Visual Knowledge oriented Programming for Interactive Knowledge Base Question Answering

no code implementations6 Jul 2023 Zijun Yao, Yuanyong Chen, Xin Lv, Shulin Cao, Amy Xin, Jifan Yu, Hailong Jin, Jianjun Xu, Peng Zhang, Lei Hou, Juanzi Li

We present Visual Knowledge oriented Programming platform (VisKoP), a knowledge base question answering (KBQA) system that integrates human into the loop to edit and debug the knowledge base (KB) queries.

Knowledge Base Question Answering Program induction +2

Learn to Not Link: Exploring NIL Prediction in Entity Linking

1 code implementation25 May 2023 Fangwei Zhu, Jifan Yu, Hailong Jin, Juanzi Li, Lei Hou, Zhifang Sui

We conduct a series of experiments with the widely used bi-encoder and cross-encoder entity linking models, results show that both types of NIL mentions in training data have a significant influence on the accuracy of NIL prediction.

Entity Linking

Preserving Knowledge Invariance: Rethinking Robustness Evaluation of Open Information Extraction

1 code implementation23 May 2023 Ji Qi, Chuchun Zhang, Xiaozhi Wang, Kaisheng Zeng, Jifan Yu, Jinxin Liu, Jiuding Sun, Yuxiang Chen, Lei Hou, Juanzi Li, Bin Xu

In this paper, we present the first benchmark that simulates the evaluation of open information extraction models in the real world, where the syntactic and expressive distributions under the same knowledge meaning may drift variously.

Language Modelling Large Language Model +1

ChatLog: Recording and Analyzing ChatGPT Across Time

1 code implementation27 Apr 2023 Shangqing Tu, Chunyang Li, Jifan Yu, Xiaozhi Wang, Lei Hou, Juanzi Li

While there are abundant researches about evaluating ChatGPT on natural language understanding and generation tasks, few studies have investigated how ChatGPT's behavior changes over time.

Natural Language Understanding

MoocRadar: A Fine-grained and Multi-aspect Knowledge Repository for Improving Cognitive Student Modeling in MOOCs

1 code implementation5 Apr 2023 Jifan Yu, Mengying Lu, Qingyang Zhong, Zijun Yao, Shangqing Tu, Zhengshan Liao, Xiaoya Li, Manli Li, Lei Hou, Hai-Tao Zheng, Juanzi Li, Jie Tang

Student modeling, the task of inferring a student's learning characteristics through their interactions with coursework, is a fundamental issue in intelligent education.

cognitive diagnosis Knowledge Tracing

GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generation

1 code implementation26 Mar 2023 Ji Qi, Jifan Yu, Teng Tu, Kunyu Gao, Yifan Xu, Xinyu Guan, Xiaozhi Wang, Yuxiao Dong, Bin Xu, Lei Hou, Juanzi Li, Jie Tang, Weidong Guo, Hui Liu, Yu Xu

Despite the recent emergence of video captioning models, how to generate vivid, fine-grained video descriptions based on the background knowledge (i. e., long and informative commentary about the domain-specific scenes with appropriate reasoning) is still far from being solved, which however has great applications such as automatic sports narrative.

Video Captioning

GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation

1 code implementation28 Feb 2023 Jing Zhang, Xiaokang Zhang, Daniel Zhang-li, Jifan Yu, Zijun Yao, Zeyao Ma, Yiqi Xu, Haohua Wang, Xiaohan Zhang, Nianyi Lin, Sunrui Lu, Juanzi Li, Jie Tang

We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable of knowledge-grounded conversation in Chinese using a search engine to access the Internet knowledge.

Dialogue Evaluation Dialogue Generation +2

ConstGCN: Constrained Transmission-based Graph Convolutional Networks for Document-level Relation Extraction

no code implementations8 Oct 2022 Ji Qi, Bin Xu, Kaisheng Zeng, Jinxin Liu, Jifan Yu, Qi Gao, Juanzi Li, Lei Hou

Document-level relation extraction with graph neural networks faces a fundamental graph construction gap between training and inference - the golden graph structure only available during training, which causes that most methods adopt heuristic or syntactic rules to construct a prior graph as a pseudo proxy.

Document-level Relation Extraction graph construction +1

Towards a General Pre-training Framework for Adaptive Learning in MOOCs

1 code implementation18 Jul 2022 Qingyang Zhong, Jifan Yu, Zheyuan Zhang, Yiming Mao, Yuquan Wang, Yankai Lin, Lei Hou, Juanzi Li, Jie Tang

Adaptive learning aims to stimulate and meet the needs of individual learners, which requires sophisticated system-level coordination of diverse tasks, including modeling learning resources, estimating student states, and making personalized recommendations.

Knowledge Tracing

Interactive Contrastive Learning for Self-supervised Entity Alignment

no code implementations17 Jan 2022 Kaisheng Zeng, Zhenhao Dong, Lei Hou, Yixin Cao, Minghao Hu, Jifan Yu, Xin Lv, Juanzi Li, Ling Feng

Self-supervised entity alignment (EA) aims to link equivalent entities across different knowledge graphs (KGs) without seed alignments.

Contrastive Learning Entity Alignment +1

Program Transfer for Answering Complex Questions over Knowledge Bases

1 code implementation ACL 2022 Shulin Cao, Jiaxin Shi, Zijun Yao, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Zhiyuan Liu, Jinghui Xiao

In this paper, we propose the approach of program transfer, which aims to leverage the valuable program annotations on the rich-resourced KBs as external supervision signals to aid program induction for the low-resourced KBs that lack program annotations.

Program induction Semantic Parsing

Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making

1 code implementation ACL 2021 Zijun Yao, Chengjiang Li, Tiansi Dong, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Yichi Zhang, Zelin Dai

Using a set of comparison features and a limited amount of annotated data, KAT Induction learns an efficient decision tree that can be interpreted by generating entity matching rules whose structure is advocated by domain experts.

Attribute Decision Making +2

MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs

no code implementations ACL 2020 Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, Wenzheng Feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu, Jie Tang

The prosperity of Massive Open Online Courses (MOOCs) provides fodder for many NLP and AI research for education applications, e. g., course concept extraction, prerequisite relation discovery, etc.

Course Concept Expansion in MOOCs with External Knowledge and Interactive Game

no code implementations ACL 2019 Jifan Yu, Chenyu Wang, Gan Luo, Lei Hou, Juanzi Li, Jie Tang, Zhiyuan Liu

As Massive Open Online Courses (MOOCs) become increasingly popular, it is promising to automatically provide extracurricular knowledge for MOOC users.

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