Publications (45)
The First Evaluation of Chinese Human-Computer Dialogue Technology
Wei-Nan Zhang, Zhigang Chen, Wanxiang Che +2
In this paper, we introduce the first evaluation of Chinese human-computer dialogue technology. We detail the evaluation scheme, tasks, metrics and how to collect and annotate the…
Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models
Runxuan Liu, Xianhao Ou, Xinyan Ma +13
Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Mode…
Generating and Exploiting Large-scale Pseudo Training Data for Zero Pronoun Resolution
Ting Liu, Yiming Cui, Qingyu Yin +3
Most existing approaches for zero pronoun resolution are heavily relying on annotated data, which is often released by shared task organizers. Therefore, the lack of annotated data…
Attention-over-Attention Neural Networks for Reading Comprehension
Yiming Cui, Zhipeng Chen, Si Wei +3
Cloze-style queries are representative problems in reading comprehension. Over the past few months, we have seen much progress that utilizing neural network approach to solve Cloze…
A Span-Extraction Dataset for Chinese Machine Reading Comprehension
Yiming Cui, Ting Liu, Wanxiang Che +5
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, the existing reading comprehension datasets are mostly in…
HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension
Zhipeng Chen, Yiming Cui, Wentao Ma +3
This paper describes the system which got the state-of-the-art results at SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge. In this paper, we present a neura…
Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams
Yiming Cui, Xin Yao, Yuxuan Qin +3
Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, mole…
MathCoPilot: An Interactive System for Human-AI Symbiotic Paradigm of Mathematical Research
Junjie Zhang, Jiayu Liu, Wenbin Liu +11
MathCoPilot is an interactive, human‑in‑the‑loop system that lets mathematicians steer AI agents to formalize and verify mathematical proofs in Lean, combining a live proof bluepri…
Memory Augmented Sequential Paragraph Retrieval for Multi-hop Question Answering
Nan Shao, Yiming Cui, Ting Liu +2
Retrieving information from correlative paragraphs or documents to answer open-domain multi-hop questions is very challenging. To deal with this challenge, most of the existing wor…
Forget Less, Generalize More: Unifying Temporal and Structural Adaptation for Dynamic Graphs
Qian Chang, Ciprian Doru Giurcaneanu, Runsong Jia +6
Representation learning on dynamic graphs requires capturing complex dependencies that evolve across both time and structure. Existing approaches typically adopt fixed temporal dec…
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive Survey
Aoran Gan, Hao Yu, Kai Zhang +5
Recent advancements in Retrieval-Augmented Generation (RAG) have revolutionized natural language processing by integrating Large Language Models (LLMs) with external information re…
Is Graph Structure Necessary for Multi-hop Question Answering?
Nan Shao, Yiming Cui, Ting Liu +2
Recently, attempting to model texts as graph structure and introducing graph neural networks to deal with it has become a trend in many NLP research areas. In this paper, we invest…
Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions
Zhipeng Chen, Yiming Cui, Wentao Ma +2
Machine Reading Comprehension (MRC) with multiple-choice questions requires the machine to read given passage and select the correct answer among several candidates. In this paper,…
Dataset for the First Evaluation on Chinese Machine Reading Comprehension
Yiming Cui, Ting Liu, Zhipeng Chen +3
Machine Reading Comprehension (MRC) has become enormously popular recently and has attracted a lot of attention. However, existing reading comprehension datasets are mostly in Engl…
Unsupervised Explanation Generation for Machine Reading Comprehension
Yiming Cui, Ting Liu, Shijin Wang +1
With the blooming of various Pre-trained Language Models (PLMs), Machine Reading Comprehension (MRC) has embraced significant improvements on various benchmarks and even surpass hu…
KCAT: A Knowledge-Constraint Typing Annotation Tool
Sheng Lin, Luye Zheng, Bo Chen +6
Fine-grained Entity Typing is a tough task which suffers from noise samples extracted from distant supervision. Thousands of manually annotated samples can achieve greater performa…
CharBERT: Character-aware Pre-trained Language Model
Wentao Ma, Yiming Cui, Chenglei Si +3
Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almos…
Improving Machine Reading Comprehension via Adversarial Training
Ziqing Yang, Yiming Cui, Wanxiang Che +3
Adversarial training (AT) as a regularization method has proved its effectiveness in various tasks, such as image classification and text classification. Though there are successfu…
CE-GOCD: Central Entity-Guided Graph Optimization for Community Detection to Augment LLM Scientific Question Answering
Jiayin Lan, Jiaqi Li, Baoxin Wang +5
Large Language Models (LLMs) are increasingly used for question answering over scientific research papers. Existing retrieval augmentation methods often rely on isolated text chunk…
SHINE: Syntax-augmented Hierarchical Interactive Encoder for Zero-shot Cross-lingual Information Extraction
Jun-Yu Ma, Jia-Chen Gu, Zhen-Hua Ling +3
Zero-shot cross-lingual information extraction(IE) aims at constructing an IE model for some low-resource target languages, given annotations exclusively in some rich-resource lang…
Transcribing Content from Structural Images with Spotlight Mechanism
Yu Yin, Zhenya Huang, Enhong Chen +4
Transcribing content from structural images, e.g., writing notes from music scores, is a challenging task as not only the content objects should be recognized, but the internal str…
Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
Ziqing Yang, Yiming Cui, Chenglei Si +4
Adversarial training (AT) as a regularization method has proved its effectiveness on various tasks. Though there are successful applications of AT on some NLP tasks, the distinguis…
Discriminative Sentence Modeling for Story Ending Prediction
Yiming Cui, Wanxiang Che, Wei-Nan Zhang +3
Story Ending Prediction is a task that needs to select an appropriate ending for the given story, which requires the machine to understand the story and sometimes needs commonsense…
Graph Retention Networks for Dynamic Graphs
Qian Chang, Xia Li, Xiufeng Cheng +4
In this paper, we propose Graph Retention Networks (GRNs) as a unified architecture for deep learning on dynamic graphs. The GRN extends the concept of retention into dynamic graph…
ChartHal: A Fine-grained Framework Evaluating Hallucination of Large Vision Language Models in Chart Understanding
Xingqi Wang, Yiming Cui, Xin Yao +3
Large Vision-Language Models (LVLMs) have recently demonstrated remarkable progress, yet hallucination remains a critical barrier, particularly in chart understanding, which requir…
From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systems
Zekun Zhou, Xiaocheng Feng, Lei Huang +11
Research is a fundamental process driving the advancement of human civilization, yet it demands substantial time and effort from researchers. In recent years, the rapid development…
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Yuxuan Zhou, Xien Liu, Chenwei Yan +8
Large language models (LLMs) have demonstrated remarkable performance on various medical benchmarks, but their capabilities across different cognitive levels remain underexplored.…
ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models
Yuqing Huang, Rongyang Zhang, Xuesong He +15
There is a growing interest in the role that LLMs play in chemistry which lead to an increased focus on the development of LLMs benchmarks tailored to chemical domains to assess th…
Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization
Lei Huang, Xiaocheng Feng, Weitao Ma +9
Ensuring contextual faithfulness in retrieval-augmented large language models (LLMs) is crucial for building trustworthy information-seeking systems, particularly in long-form ques…
Cross-Lingual Machine Reading Comprehension
Yiming Cui, Wanxiang Che, Ting Liu +3
Though the community has made great progress on Machine Reading Comprehension (MRC) task, most of the previous works are solving English-based MRC problems, and there are few effor…
SparkRA: A Retrieval-Augmented Knowledge Service System Based on Spark Large Language Model
Dayong Wu, Jiaqi Li, Baoxin Wang +10
Large language models (LLMs) have shown remarkable achievements across various language tasks.To enhance the performance of LLMs in scientific literature services, we developed the…
A Sentence Cloze Dataset for Chinese Machine Reading Comprehension
Yiming Cui, Ting Liu, Ziqing Yang +5
Owing to the continuous efforts by the Chinese NLP community, more and more Chinese machine reading comprehension datasets become available. To add diversity in this area, in this…
Multi-Stage Coarse-to-Fine Contrastive Learning for Conversation Intent Induction
Caiyuan Chu, Ya Li, Yifan Liu +4
Intent recognition is critical for task-oriented dialogue systems. However, for emerging domains and new services, it is difficult to accurately identify the key intent of a conver…
Learning Dynamic Context Augmentation for Global Entity Linking
Xiyuan Yang, Xiaotao Gu, Sheng Lin +6
Despite of the recent success of collective entity linking (EL) methods, these "global" inference methods may yield sub-optimal results when the "all-mention coherence" assumption…
TripleNet: Triple Attention Network for Multi-Turn Response Selection in Retrieval-based Chatbots
Wentao Ma, Yiming Cui, Nan Shao +5
We consider the importance of different utterances in the context for selecting the response usually depends on the current query. In this paper, we propose the model TripleNet to…
Consensus Attention-based Neural Networks for Chinese Reading Comprehension
Yiming Cui, Ting Liu, Zhipeng Chen +2
Reading comprehension has embraced a booming in recent NLP research. Several institutes have released the Cloze-style reading comprehension data, and these have greatly accelerated…
Revisiting Pre-Trained Models for Chinese Natural Language Processing
Yiming Cui, Wanxiang Che, Ting Liu +3
Bidirectional Encoder Representations from Transformers (BERT) has shown marvelous improvements across various NLP tasks, and consecutive variants have been proposed to further imp…
Contextual Recurrent Units for Cloze-style Reading Comprehension
Yiming Cui, Wei-Nan Zhang, Wanxiang Che +4
Recurrent Neural Networks (RNN) are known as powerful models for handling sequential data, and especially widely utilized in various natural language processing tasks. In this pape…
Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering
Bo Chen, Xiaotao Gu, Yufeng Hu +4
Recently, distant supervision has gained great success on Fine-grained Entity Typing (FET). Despite its efficiency in reducing manual labeling efforts, it also brings the challenge…
SportsSum2.0: Generating High-Quality Sports News from Live Text Commentary
Jiaan Wang, Zhixu Li, Qiang Yang +4
Sports game summarization aims to generate news articles from live text commentaries. A recent state-of-the-art work, SportsSum, not only constructs a large benchmark dataset, but…
JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving
Wayne Xin Zhao, Kun Zhou, Beichen Zhang +8
Although pre-trained language models~(PLMs) have recently advanced the research progress in mathematical reasoning, they are not specially designed as a capable multi-task solver,…
Conversational Word Embedding for Retrieval-Based Dialog System
Wentao Ma, Yiming Cui, Ting Liu +3
Human conversations contain many types of information, e.g., knowledge, common sense, and language habits. In this paper, we propose a conversational word embedding method named PR…
TextBrewer: An Open-Source Knowledge Distillation Toolkit for Natural Language Processing
Ziqing Yang, Yiming Cui, Zhipeng Chen +4
In this paper, we introduce TextBrewer, an open-source knowledge distillation toolkit designed for natural language processing. It works with different neural network models and su…
GIFT: Graph-Induced Fine-Tuning for Multi-Party Conversation Understanding
Jia-Chen Gu, Zhen-Hua Ling, Quan Liu +2
Addressing the issues of who saying what to whom in multi-party conversations (MPCs) has recently attracted a lot of research attention. However, existing methods on MPC understand…
EKT: Exercise-aware Knowledge Tracing for Student Performance Prediction
Qi Liu, Zhenya Huang, Yu Yin +4
For offering proactive services to students in intelligent education, one of the fundamental tasks is predicting their performance (e.g., scores) on future exercises, where it is n…