Yulia Tsvetkov

research

∙ 06/26/2023

Understanding In-Context Learning via Supportive Pretraining Data

In-context learning (ICL) improves language models' performance on a var...

0 Xiaochuang Han, et al. ∙

research

∙ 05/30/2023

Examining risks of racial biases in NLP tools for child protective services

Although much literature has established the presence of demographic bia...

0 Anjalie Field, et al. ∙

research

∙ 05/24/2023

BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer

Despite remarkable advancements in few-shot generalization in natural la...

0 Akari Asai, et al. ∙

research

∙ 05/24/2023

Trusting Your Evidence: Hallucinate Less with Context-aware Decoding

Language models (LMs) often struggle to pay enough attention to the inpu...

0 Weijia Shi, et al. ∙

research

∙ 05/24/2023

GlobalBench: A Benchmark for Global Progress in Natural Language Processing

Despite the major advances in NLP, significant disparities in NLP system...

0 Yueqi Song, et al. ∙

research

∙ 05/23/2023

TalkUp: A Novel Dataset Paving the Way for Understanding Empowering Language

Empowering language is important in many real-world contexts, from educa...

0 Lucille Njoo, et al. ∙

research

∙ 05/17/2023

Can Language Models Solve Graph Problems in Natural Language?

Large language models (LLMs) are increasingly adopted for a variety of t...

0 Heng Wang, et al. ∙

research

∙ 05/17/2023

CooK: Empowering General-Purpose Language Models with Modular and Collaborative Knowledge

Large language models (LLMs) are increasingly adopted for knowledge-inte...

0 Shangbin Feng, et al. ∙

research

∙ 05/15/2023

From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models

Large language models (LMs) are pretrained on diverse data sources: news...

0 Shangbin Feng, et al. ∙

research

∙ 05/14/2023

FactKB: Generalizable Factuality Evaluation using Language Models Enhanced with Factual Knowledge

Evaluating the factual consistency of automatically generated summaries ...

0 Shangbin Feng, et al. ∙

research

∙ 12/20/2022

Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too?

Large language models can perform new tasks in a zero-shot fashion, give...

0 Weijia Shi, et al. ∙

research

∙ 10/27/2022

Gendered Mental Health Stigma in Masked Language Models

Mental health stigma prevents many individuals from receiving the approp...

0 Inna Wanyin Lin, et al. ∙

research

∙ 10/22/2022

Correcting Diverse Factual Errors in Abstractive Summarization via Post-Editing and Language Model Infilling

Abstractive summarization models often generate inconsistent summaries c...

0 Vidhisha Balachandran, et al. ∙

research

∙ 10/08/2022

KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document Understanding

With the advent of pre-trained language models (LMs), increasing researc...

0 Shangbin Feng, et al. ∙

research

∙ 05/25/2022

ORCA: Interpreting Prompted Language Models via Locating Supporting Data Evidence in the Ocean of Pretraining Data

Large pretrained language models have been performing increasingly well ...

0 Xiaochuang Han, et al. ∙

research

∙ 05/24/2022

VoynaSlov: A Data Set of Russian Social Media Activity during the 2022 Ukraine-Russia War

In this report, we describe a new data set called VoynaSlov which contai...

0 Chan Young Park, et al. ∙

research

∙ 03/16/2022

Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching

Natural language processing (NLP) models trained on people-generated dat...

0 Alissa Ostapenko, et al. ∙

research

∙ 03/15/2022

Unsupervised Keyphrase Extraction via Interpretable Neural Networks

Keyphrase extraction aims at automatically extracting a list of "importa...

8 Rishabh Joshi, et al. ∙

research

∙ 10/09/2021

Detecting Community Sensitive Norm Violations in Online Conversations

Online platforms and communities establish their own norms that govern w...

8 Chan Young Park, et al. ∙

research

∙ 10/07/2021

Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates

Among the most critical limitations of deep learning NLP models are thei...

0 Xiaochuang Han, et al. ∙

research

∙ 09/20/2021

Improving Span Representation for Domain-adapted Coreference Resolution

Recent work has shown fine-tuning neural coreference models can produce ...

0 Nupoor Gandhi, et al. ∙

research

∙ 09/10/2021

Efficient Test Time Adapter Ensembling for Low-resource Language Varieties

Adapters are light-weight modules that allow parameter-efficient fine-tu...

0 Xinyi Wang, et al. ∙

research

∙ 08/24/2021

SimVLM: Simple Visual Language Model Pretraining with Weak Supervision

With recent progress in joint modeling of visual and textual representat...

6 Zirui Wang, et al. ∙

research

∙ 06/21/2021

A Survey of Race, Racism, and Anti-Racism in NLP

Despite inextricable ties between race and language, little work has con...

0 Anjalie Field, et al. ∙

research

∙ 06/10/2021

Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation

Open-domain neural dialogue models have achieved high performance in res...

10 Prakhar Gupta, et al. ∙

research

∙ 06/02/2021

DialoGraph: Incorporating Interpretable Strategy-Graph Networks into Negotiation Dialogues

To successfully negotiate a deal, it is not enough to communicate fluent...

9 Rishabh Joshi, et al. ∙

research

∙ 04/27/2021

Understanding Factuality in Abstractive Summarization with FRANK: A Benchmark for Factuality Metrics

Modern summarization models generate highly fluent but often factually u...

4 Artidoro Pagnoni, et al. ∙

research

∙ 04/18/2021

Simple and Efficient ways to Improve REALM

Dense retrieval has been shown to be effective for retrieving relevant d...

0 Vidhisha Balachandran, et al. ∙

research

∙ 03/30/2021

Evaluating the Morphosyntactic Well-formedness of Generated Texts

Text generation systems are ubiquitous in natural language processing ap...

0 Adithya Pratapa, et al. ∙

research

∙ 12/31/2020

Controlled Analyses of Social Biases in Wikipedia Bios

Social biases on Wikipedia, a widely-read global platform, could greatly...

0 Anjalie Field, et al. ∙

research

∙ 10/21/2020

Multilingual Contextual Affective Analysis of LGBT People Portrayals in Wikipedia

Specific lexical choices in how people are portrayed both reflect the wr...

0 Chan Young Park, et al. ∙

research

∙ 10/12/2020

Gradient Vaccine: Investigating and Improving Multi-task Optimization in Massively Multilingual Models

Massively multilingual models subsuming tens or even hundreds of languag...

3 Zirui Wang, et al. ∙

research

∙ 10/07/2020

Fortifying Toxic Speech Detectors Against Veiled Toxicity

Modern toxic speech detectors are incompetent in recognizing disguised o...

0 Xiaochuang Han, et al. ∙

research

∙ 10/06/2020

On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment

Modern multilingual models are trained on concatenated text from multipl...

0 Zirui Wang, et al. ∙

research

∙ 10/02/2020

Automatic Extraction of Rules Governing Morphological Agreement

Creating a descriptive grammar of a language is an indispensable step fo...

0 Aditi Chaudhary, et al. ∙

research

∙ 08/20/2020

Controlling Dialogue Generation with Semantic Exemplars

Dialogue systems pretrained with large language models generate locally ...

0 Prakhar Gupta, et al. ∙

research

∙ 08/11/2020

LTIatCMU at SemEval-2020 Task 11: Incorporating Multi-Level Features for Multi-Granular Propaganda Span Identification

In this paper we describe our submission for the task of Propaganda Span...

0 Sopan Khosla, et al. ∙

research

∙ 06/16/2020

Ranking Transfer Languages with Pragmatically-Motivated Features for Multilingual Sentiment Analysis

Cross-lingual transfer learning studies how datasets, annotations, and m...

0 Jimin Sun, et al. ∙

research

∙ 05/25/2020

Demoting Racial Bias in Hate Speech Detection

In current hate speech datasets, there exists a high correlation between...

0 Mengzhou Xia, et al. ∙

research

∙ 05/20/2020

A Computational Analysis of Polarization on Indian and Pakistani Social Media

Between February 14, 2019 and March 4, 2019, a terrorist attack in Pulwa...

0 Aman Tyagi, et al. ∙

research

∙ 05/14/2020

Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions

Modern deep learning models for NLP are notoriously opaque. This has mot...

0 Xiaochuang Han, et al. ∙

research

∙ 04/17/2020

Unsupervised Discovery of Implicit Gender Bias

Despite their prevalence in society, social biases are difficult to defi...

0 Anjalie Field, et al. ∙

research

∙ 04/14/2020

Balancing Training for Multilingual Neural Machine Translation

When training multilingual machine translation (MT) models that can tran...

0 Xinyi Wang, et al. ∙

research

∙ 03/06/2020

A Framework for the Computational Linguistic Analysis of Dehumanization

Dehumanization is a pernicious psychological process that often leads to...

0 Julia Mendelsohn, et al. ∙

research

∙ 03/01/2020

StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization

Traditional preneural approaches to single document summarization relied...

0 Vidhisha Balachandran, et al. ∙

research

∙ 01/21/2020

Where New Words Are Born: Distributional Semantic Analysis of Neologisms and Their Semantic Neighborhoods

We perform statistical analysis of the phenomenon of neology, the proces...

0 Maria Ryskina, et al. ∙

research

∙ 09/30/2019

A Dynamic Strategy Coach for Effective Negotiation

Negotiation is a complex activity involving strategic reasoning, persuas...

0 Yiheng Zhou, et al. ∙

research

∙ 09/30/2019

Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History

We study non-collaborative dialogs, where two agents have a conflict of ...

0 Yiheng Zhou, et al. ∙

research

∙ 09/01/2019

Topics to Avoid: Demoting Latent Confounds in Text Classification

Despite impressive performance on many text classification tasks, deep n...

2 Sachin Kumar, et al. ∙

research

∙ 07/23/2019

CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology

This paper presents the submission by the CMU-01 team to the SIGMORPHON ...

0 Aditi Chaudhary, et al. ∙

Yulia Tsvetkov

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