Search Results for author: Wenlin Yao

Found 22 papers, 12 papers with code

Weakly Supervised Subevent Knowledge Acquisition

no code implementations EMNLP 2020 Wenlin Yao, Zeyu Dai, Maitreyi Ramaswamy, Bonan Min, Ruihong Huang

We first obtain the initial set of event pairs that are likely to have the subevent relation, by exploiting two observations that 1) subevents are temporally contained by the parent event, and 2) the definitions of the parent event can be used to further guide the identification of subevents.

MMC: Advancing Multimodal Chart Understanding with Large-scale Instruction Tuning

1 code implementation15 Nov 2023 Fuxiao Liu, Xiaoyang Wang, Wenlin Yao, Jianshu Chen, Kaiqiang Song, Sangwoo Cho, Yaser Yacoob, Dong Yu

Recognizing the need for a comprehensive evaluation of LMM chart understanding, we also propose a MultiModal Chart Benchmark (MMC-Benchmark), a comprehensive human-annotated benchmark with 9 distinct tasks evaluating reasoning capabilities over charts.

TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs

1 code implementation9 Nov 2023 Shuyi Xie, Wenlin Yao, Yong Dai, Shaobo Wang, Donlin Zhou, Lifeng Jin, Xinhua Feng, Pengzhi Wei, Yujie Lin, Zhichao Hu, Dong Yu, Zhengyou Zhang, Jing Nie, Yuhong Liu

We construct a hierarchical task tree encompassing 7 major areas covering over 200 categories and over 800 tasks, which covers diverse capabilities such as question answering, reasoning, multiturn dialogue, and text generation, to evaluate LLMs in a comprehensive and in-depth manner.

Benchmarking Question Answering +1

A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation

no code implementations8 Jul 2023 Neeraj Varshney, Wenlin Yao, Hongming Zhang, Jianshu Chen, Dong Yu

Specifically, the detection technique achieves a recall of ~88% and the mitigation technique successfully mitigates 57. 6% of the correctly detected hallucinations.

Towards Personalized Cold-Start Recommendation with Prompts

1 code implementation29 Jun 2023 Xuansheng Wu, Huachi Zhou, Yucheng Shi, Wenlin Yao, Xiao Huang, Ninghao Liu

Recommender systems play a crucial role in helping users discover information that aligns with their interests based on their past behaviors.

Recommendation Systems Sentiment Analysis

ZeroKBC: A Comprehensive Benchmark for Zero-Shot Knowledge Base Completion

1 code implementation6 Dec 2022 Pei Chen, Wenlin Yao, Hongming Zhang, Xiaoman Pan, Dian Yu, Dong Yu, Jianshu Chen

However, there has been limited research on the zero-shot KBC settings, where we need to deal with unseen entities and relations that emerge in a constantly growing knowledge base.

Knowledge Base Completion Knowledge Graphs

NarraSum: A Large-Scale Dataset for Abstractive Narrative Summarization

1 code implementation2 Dec 2022 Chao Zhao, Faeze Brahman, Kaiqiang Song, Wenlin Yao, Dian Yu, Snigdha Chaturvedi

To encourage research in this direction, we propose NarraSum, a large-scale narrative summarization dataset.

Natural Language Understanding

Efficient Zero-shot Event Extraction with Context-Definition Alignment

1 code implementation9 Nov 2022 Hongming Zhang, Wenlin Yao, Dong Yu

We argue that using the static embedding of the event type name might not be enough because a single word could be ambiguous, and we need a sentence to define the type semantics accurately.

Contrastive Learning Zero-shot Event Extraction

Knowledge-in-Context: Towards Knowledgeable Semi-Parametric Language Models

no code implementations28 Oct 2022 Xiaoman Pan, Wenlin Yao, Hongming Zhang, Dian Yu, Dong Yu, Jianshu Chen

In this paper, we develop a novel semi-parametric language model architecture, Knowledge-in-Context (KiC), which empowers a parametric text-to-text language model with a knowledge-rich external memory.

Language Modelling World Knowledge

Salience Allocation as Guidance for Abstractive Summarization

1 code implementation22 Oct 2022 Fei Wang, Kaiqiang Song, Hongming Zhang, Lifeng Jin, Sangwoo Cho, Wenlin Yao, Xiaoyang Wang, Muhao Chen, Dong Yu

Recent literature adds extractive summaries as guidance for abstractive summarization models to provide hints of salient content and achieves better performance.

Abstractive Text Summarization

Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination

1 code implementation21 Oct 2022 Yue Yang, Wenlin Yao, Hongming Zhang, Xiaoyang Wang, Dong Yu, Jianshu Chen

Large-scale pretrained language models have made significant advances in solving downstream language understanding tasks.

Language Modelling Retrieval +1

Learning-by-Narrating: Narrative Pre-Training for Zero-Shot Dialogue Comprehension

1 code implementation ACL 2022 Chao Zhao, Wenlin Yao, Dian Yu, Kaiqiang Song, Dong Yu, Jianshu Chen

Comprehending a dialogue requires a model to capture diverse kinds of key information in the utterances, which are either scattered around or implicitly implied in different turns of conversations.

Connect-the-Dots: Bridging Semantics between Words and Definitions via Aligning Word Sense Inventories

2 code implementations EMNLP 2021 Wenlin Yao, Xiaoman Pan, Lifeng Jin, Jianshu Chen, Dian Yu, Dong Yu

We then train a model to identify semantic equivalence between a target word in context and one of its glosses using these aligned inventories, which exhibits strong transfer capability to many WSD tasks.

Word Sense Disambiguation

Weakly-supervised Fine-grained Event Recognition on Social Media Texts for Disaster Management

1 code implementation4 Oct 2020 Wenlin Yao, Cheng Zhang, Shiva Saravanan, Ruihong Huang, Ali Mostafavi

People increasingly use social media to report emergencies, seek help or share information during disasters, which makes social networks an important tool for disaster management.


Temporal Event Knowledge Acquisition via Identifying Narratives

no code implementations ACL 2018 Wenlin Yao, Ruihong Huang

Inspired by the double temporality characteristic of narrative texts, we propose a novel approach for acquiring rich temporal "before/after" event knowledge across sentences in narrative stories.

General Classification Relation Classification +1

Using Context Events in Neural Network Models for Event Temporal Status Identification

no code implementations IJCNLP 2017 Zeyu Dai, Wenlin Yao, Ruihong Huang

Focusing on the task of identifying event temporal status, we find that events directly or indirectly governing the target event in a dependency tree are most important contexts.

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