554 citations · 1.3k across the 62 of their papers we have counts for
48 papers · 1 filter
Automatic Evaluation for Text-to-image Generation: Task-decomposed Framework, Distilled Training, and Meta-evaluation Benchmark
Rong-Cheng Tu, Zi-Ao Ma, Tian Lan +3
Driven by the remarkable progress in diffusion models, text-to-image generation has made significant strides, creating a pressing demand for automatic quality evaluation of generat…
Training Language Models to Critique With Multi-agent Feedback
Tian Lan, Wenwei Zhang, Chengqi Lyu +6
Critique ability, a meta-cognitive capability of humans, presents significant challenges for LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using crit…
Beyond Exact Match: Semantically Reassessing Event Extraction by Large Language Models
Yi-Fan Lu, Xian-Ling Mao, Tian Lan +3
Event extraction has gained extensive research attention due to its broad range of applications. However, the current mainstream evaluation method for event extraction relies on to…
EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain
Yi-Fan Lu, Xian-Ling Mao, Bo Wang +2
It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, finance, and biology. However, event e…
Mix-Initiative Response Generation with Dynamic Prefix Tuning
Yuxiang Nie, Heyan Huang, Xian-Ling Mao +1
Mixed initiative serves as one of the key factors in controlling conversation directions. For a speaker, responding passively or leading proactively would result in rather differen…
CriticEval: Evaluating Large Language Model as Critic
Tian Lan, Wenwei Zhang, Chen Xu +4
Critique ability, i.e., the capability of Large Language Models (LLMs) to identify and rectify flaws in responses, is crucial for their applications in self-improvement and scalabl…
Copy Is All You Need
Tian Lan, Deng Cai, Yan Wang +2
The dominant text generation models compose the output by sequentially selecting words from a fixed vocabulary. In this paper, we formulate text generation as progressively copying…
SciMRC: Multi-perspective Scientific Machine Reading Comprehension
Xiao Zhang, Heqi Zheng, Yuxiang Nie +2
Scientific machine reading comprehension (SMRC) aims to understand scientific texts through interactions with humans by given questions. As far as we know, there is only one datase…
Measuring Cross-Lingual Transferability of Multilingual Transformers on Sentence Classification
Zewen Chi, Heyan Huang, Xian-Ling Mao
Recent studies have exhibited remarkable capabilities of pre-trained multilingual Transformers, especially cross-lingual transferability. However, current methods do not measure cr…
AttenWalker: Unsupervised Long-Document Question Answering via Attention-based Graph Walking
Yuxiang Nie, Heyan Huang, Wei Wei +1
Annotating long-document question answering (long-document QA) pairs is time-consuming and expensive. To alleviate the problem, it might be possible to generate long-document QA pa…
Bridging The Gap: Entailment Fused-T5 for Open-retrieval Conversational Machine Reading Comprehension
Xiao Zhang, Heyan Huang, Zewen Chi +1
Open-retrieval conversational machine reading comprehension (OCMRC) simulates real-life conversational interaction scenes. Machines are required to make a decision of "Yes/No/Inqui…
Momentum Decoding: Open-ended Text Generation As Graph Exploration
Tian Lan, Yixuan Su, Shuhang Liu +2
Open-ended text generation with autoregressive language models (LMs) is one of the core tasks in natural language processing. However, maximization-based decoding methods (e.g., gr…
ET5: A Novel End-to-end Framework for Conversational Machine Reading Comprehension
Xiao Zhang, Heyan Huang, Zewen Chi +1
Conversational machine reading comprehension (CMRC) aims to assist computers to understand an natural language text and thereafter engage in a multi-turn conversation to answer que…
Unsupervised Question Answering via Answer Diversifying
Yuxiang Nie, Heyan Huang, Zewen Chi +1
Unsupervised question answering is an attractive task due to its independence on labeled data. Previous works usually make use of heuristic rules as well as pre-trained models to c…
Cross-Lingual Phrase Retrieval
Heqi Zheng, Xiao Zhang, Zewen Chi +5
Cross-lingual retrieval aims to retrieve relevant text across languages. Current methods typically achieve cross-lingual retrieval by learning language-agnostic text representation…
On the Representation Collapse of Sparse Mixture of Experts
Zewen Chi, Li Dong, Shaohan Huang +9
Sparse mixture of experts provides larger model capacity while requiring a constant computational overhead. It employs the routing mechanism to distribute input tokens to the best-…
BiSyn-GAT+: Bi-Syntax Aware Graph Attention Network for Aspect-based Sentiment Analysis
Shuo Liang, Wei Wei, Xian-Ling Mao +2
Aspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that aims to align aspects and corresponding sentiments for aspect-specific sentiment polarity infe…
OneRel:Joint Entity and Relation Extraction with One Module in One Step
Yu-Ming Shang, Heyan Huang, Xian-Ling Mao
Joint entity and relation extraction is an essential task in natural language processing and knowledge graph construction. Existing approaches usually decompose the joint extractio…
Exploring Dense Retrieval for Dialogue Response Selection
Tian Lan, Deng Cai, Yan Wang +3
Recent progress in deep learning has continuously improved the accuracy of dialogue response selection. In particular, sophisticated neural network architectures are leveraged to c…
Cross-Lingual Language Model Meta-Pretraining
Zewen Chi, Heyan Huang, Luyang Liu +2
The success of pretrained cross-lingual language models relies on two essential abilities, i.e., generalization ability for learning downstream tasks in a source language, and cros…
Context-aware Entity Typing in Knowledge Graphs
Weiran Pan, Wei Wei, Xian-Ling Mao
Knowledge graph entity typing aims to infer entities' missing types in knowledge graphs which is an important but under-explored issue. This paper proposes a novel method for this…
Emotion-aware Chat Machine: Automatic Emotional Response Generation for Human-like Emotional Interaction
Wei Wei, Jiayi Liu, Xianling Mao +4
The consistency of a response to a given post at semantic-level and emotional-level is essential for a dialogue system to deliver human-like interactions. However, this challenge i…
Exploiting Global Contextual Information for Document-level Named Entity Recognition
Zanbo Wang, Wei Wei, Xianling Mao +4
Most existing named entity recognition (NER) approaches are based on sequence labeling models, which focus on capturing the local context dependencies. However, the way of taking o…
XLM-E: Cross-lingual Language Model Pre-training via ELECTRA
Zewen Chi, Shaohan Huang, Li Dong +8
In this paper, we introduce ELECTRA-style tasks to cross-lingual language model pre-training. Specifically, we present two pre-training tasks, namely multilingual replaced token de…