Search Results for author: Alan Ritter

Found 52 papers, 27 papers with code

Improved Instruction Ordering in Recipe-Grounded Conversation

1 code implementation26 May 2023 Duong Minh Le, Ruohao Guo, Wei Xu, Alan Ritter

In this paper, we study the task of instructional dialogue and focus on the cooking domain.

Intent Detection Response Generation

Schema-Driven Information Extraction from Heterogeneous Tables

1 code implementation23 May 2023 Fan Bai, Junmo Kang, Gabriel Stanovsky, Dayne Freitag, Alan Ritter

To assess various LLM's capabilities on this task, we develop a benchmark composed of tables from three diverse domains: machine learning papers, chemistry tables, and webpages.

Attribute Extraction Instruction Following +1

Are Large Language Models Robust Zero-shot Coreference Resolvers?

no code implementations23 May 2023 Nghia T. Le, Alan Ritter

At the same time, pre-trained large language models (LMs) have exhibited strong zero- and few-shot learning abilities across a wide range of NLP tasks including pronoun resolution.

coreference-resolution Coreference Resolution +3

Distill or Annotate? Cost-Efficient Fine-Tuning of Compact Models

no code implementations2 May 2023 Junmo Kang, Wei Xu, Alan Ritter

Fine-tuning large models is highly effective, however, inference using these models can be expensive and produces carbon emissions.

Knowledge Distillation

Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?

no code implementations23 Feb 2023 Yang Chen, Hexiang Hu, Yi Luan, Haitian Sun, Soravit Changpinyo, Alan Ritter, Ming-Wei Chang

Our analysis shows that it is challenging for the state-of-the-art multi-modal pre-trained models to answer visual information seeking questions, but this capability is improved through fine-tuning on the automated InfoSeek dataset.

Common Sense Reasoning Question Answering +1

Human-in-the-loop Evaluation for Early Misinformation Detection: A Case Study of COVID-19 Treatments

1 code implementation19 Dec 2022 Ethan Mendes, Yang Chen, Alan Ritter, Wei Xu

We present a human-in-the-loop evaluation framework for fact-checking novel misinformation claims and identifying social media messages that support them.

Fact Checking Misinformation

Frustratingly Easy Label Projection for Cross-lingual Transfer

1 code implementation28 Nov 2022 Yang Chen, Chao Jiang, Alan Ritter, Wei Xu

Translating training data into many languages has emerged as a practical solution for improving cross-lingual transfer.

Cross-Lingual Transfer NER +3

Stanceosaurus: Classifying Stance Towards Multilingual Misinformation

no code implementations28 Oct 2022 Jonathan Zheng, Ashutosh Baheti, Tarek Naous, Wei Xu, Alan Ritter

We present Stanceosaurus, a new corpus of 28, 033 tweets in English, Hindi, and Arabic annotated with stance towards 251 misinformation claims.

Domain Adaptation Fact Checking +1

Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context Experts

1 code implementation7 Oct 2022 Nghia T. Le, Fan Bai, Alan Ritter

As far as we are aware, this is the first work to present experimental results demonstrating the effectiveness of in-context learning on the task of few-shot anaphora resolution in scientific protocols.

Language Modelling Retrieval

SynKB: Semantic Search for Synthetic Procedures

1 code implementation15 Aug 2022 Fan Bai, Alan Ritter, Peter Madrid, Dayne Freitag, John Niekrasz

In this paper we present SynKB, an open-source, automatically extracted knowledge base of chemical synthesis protocols.

Pre-train or Annotate? Domain Adaptation with a Constrained Budget

1 code implementation EMNLP 2021 Fan Bai, Alan Ritter, Wei Xu

Our experiments suggest task-specific data annotation should be part of an economical strategy when adapting an NLP model to a new domain.

Domain Adaptation

Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts

1 code implementation EMNLP 2021 Ashutosh Baheti, Maarten Sap, Alan Ritter, Mark Riedl

To better understand the dynamics of contextually offensive language, we investigate the stance of dialogue model responses in offensive Reddit conversations.

Dialogue Generation

Process-Level Representation of Scientific Protocols with Interactive Annotation

2 code implementations EACL 2021 Ronen Tamari, Fan Bai, Alan Ritter, Gabriel Stanovsky

We develop Process Execution Graphs (PEG), a document-level representation of real-world wet lab biochemistry protocols, addressing challenges such as cross-sentence relations, long-range coreference, grounding, and implicit arguments.

Relation Extraction

Model Selection for Cross-Lingual Transfer

1 code implementation EMNLP 2021 Yang Chen, Alan Ritter

Transformers that are pre-trained on multilingual corpora, such as, mBERT and XLM-RoBERTa, have achieved impressive cross-lingual transfer capabilities.

Meta-Learning Model Selection +2

Model Selection for Cross-Lingual Transfer using a Learned Scoring Function

no code implementations28 Sep 2020 Yang Chen, Alan Ritter

In the zero-shot cross-lingual transfer setting, only English training data is assumed, and the fine-tuned model is evaluated on another target language.

Model Selection Transfer Learning +1

Measuring Forecasting Skill from Text

1 code implementation ACL 2020 Shi Zong, Alan Ritter, Eduard Hovy

We present a number of linguistic metrics which are computed over text associated with people's predictions about the future including: uncertainty, readability, and emotion.

Extracting a Knowledge Base of COVID-19 Events from Social Media

2 code implementations COLING 2022 Shi Zong, Ashutosh Baheti, Wei Xu, Alan Ritter

In this paper, we present a manually annotated corpus of 10, 000 tweets containing public reports of five COVID-19 events, including positive and negative tests, deaths, denied access to testing, claimed cures and preventions.

Extracting COVID-19 Events from Twitter slot-filling

Fluent Response Generation for Conversational Question Answering

1 code implementation ACL 2020 Ashutosh Baheti, Alan Ritter, Kevin Small

In this work, we propose a method for situating QA responses within a SEQ2SEQ NLG approach to generate fluent grammatical answer responses while maintaining correctness.

Conversational Question Answering Data Augmentation +3

Code and Named Entity Recognition in StackOverflow

1 code implementation ACL 2020 Jeniya Tabassum, Mounica Maddela, Wei Xu, Alan Ritter

We also present the SoftNER model which achieves an overall 79. 10 F$_1$ score for code and named entity recognition on StackOverflow data.

named-entity-recognition Named Entity Recognition +1

An Empirical Study of Pre-trained Transformers for Arabic Information Extraction

1 code implementation EMNLP 2020 Wuwei Lan, Yang Chen, Wei Xu, Alan Ritter

Multilingual pre-trained Transformers, such as mBERT (Devlin et al., 2019) and XLM-RoBERTa (Conneau et al., 2020a), have been shown to enable the effective cross-lingual zero-shot transfer.

Cross-Lingual Transfer Language Modelling +10

SemEval-2013 Task 2: Sentiment Analysis in Twitter

no code implementations SEMEVAL 2013 Preslav Nakov, Zornitsa Kozareva, Alan Ritter, Sara Rosenthal, Veselin Stoyanov, Theresa Wilson

To address this issue, we have proposed SemEval-2013 Task 2: Sentiment Analysis in Twitter, which included two subtasks: A, an expression-level subtask, and B, a message-level subtask.

Sentiment Analysis

Structured Minimally Supervised Learning for Neural Relation Extraction

1 code implementation NAACL 2019 Fan Bai, Alan Ritter

Our approach achieves state-of-the-art results on minimally supervised sentential relation extraction, outperforming a number of baselines, including a competitive approach that uses the attention layer of a purely neural model.

Relation Extraction

Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media

1 code implementation NAACL 2019 Shi Zong, Alan Ritter, Graham Mueller, Evan Wright

In this paper, we investigate methods to analyze the severity of cybersecurity threats based on the language that is used to describe them online.

Adversarial Learning for Neural Dialogue Generation

8 code implementations EMNLP 2017 Jiwei Li, Will Monroe, Tianlin Shi, Sébastien Jean, Alan Ritter, Dan Jurafsky

In this paper, drawing intuition from the Turing test, we propose using adversarial training for open-domain dialogue generation: the system is trained to produce sequences that are indistinguishable from human-generated dialogue utterances.

Dialogue Evaluation Dialogue Generation +1

Results of the WNUT16 Named Entity Recognition Shared Task

no code implementations WS 2016 Benjamin Strauss, Bethany Toma, Alan Ritter, Marie-Catherine de Marneffe, Wei Xu

This paper presents the results of the Twitter Named Entity Recognition shared task associated with W-NUT 2016: a named entity tagging task with 10 teams participating.

Named Entity Recognition Named Entity Recognition (NER)

TweeTime: A Minimally Supervised Method for Recognizing and Normalizing Time Expressions in Twitter

1 code implementation9 Aug 2016 Jeniya Tabassum, Alan Ritter, Wei Xu

We describe TweeTIME, a temporal tagger for recognizing and normalizing time expressions in Twitter.

Deep Reinforcement Learning for Dialogue Generation

8 code implementations EMNLP 2016 Jiwei Li, Will Monroe, Alan Ritter, Michel Galley, Jianfeng Gao, Dan Jurafsky

Recent neural models of dialogue generation offer great promise for generating responses for conversational agents, but tend to be shortsighted, predicting utterances one at a time while ignoring their influence on future outcomes.

Dialogue Generation Policy Gradient Methods +2

Learning multi-faceted representations of individuals from heterogeneous evidence using neural networks

no code implementations18 Oct 2015 Jiwei Li, Alan Ritter, Dan Jurafsky

Inferring latent attributes of people online is an important social computing task, but requires integrating the many heterogeneous sources of information available on the web.

Community Detection Link Prediction

Sense Discovery via Co-Clustering on Images and Text

no code implementations CVPR 2015 Xinlei Chen, Alan Ritter, Abhinav Gupta, Tom Mitchell

We present a co-clustering framework that can be used to discover multiple semantic and visual senses of a given Noun Phrase (NP).

Inferring User Preferences by Probabilistic Logical Reasoning over Social Networks

no code implementations11 Nov 2014 Jiwei Li, Alan Ritter, Dan Jurafsky

by building a probabilistic model that reasons over user attributes (the user's location or gender) and the social network (the user's friends and spouse), via inferences like homophily (I am more likely to like sushi if spouse or friends like sushi, I am more likely to like the Knicks if I live in New York).

Logical Reasoning Relation Extraction

Extracting Lexically Divergent Paraphrases from Twitter

1 code implementation TACL 2014 Wei Xu, Alan Ritter, Chris Callison-Burch, William B. Dolan, Yangfeng Ji

We present MultiP (Multi-instance Learning Paraphrase Model), a new model suited to identify paraphrases within the short messages on Twitter.

Modeling Missing Data in Distant Supervision for Information Extraction

no code implementations TACL 2013 Alan Ritter, Luke Zettlemoyer, {Mausam}, Oren Etzioni

Distant supervision algorithms learn information extraction models given only large readily available databases and text collections.

Relation Extraction

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