NAACL 2024

1,282 papers

Lexicans at Chemotimelines 2024: Chemotimeline Chronicles - Leveraging Large Language Models (LLMs) for Temporal Relations Extraction in Oncological Electronic Health Records

Vishakha Sharma, Andrés Fernández, Andrei Ioanovici, David Talby, Frederik Buijs

LAILab at Chemotimelines 2024: Finetuning sequence-to-sequence language models for temporal relation extraction towards cancer patient undergoing chemotherapy treatment

Shohreh Haddadan, Tuan-Dung Le, Thanh Duong, Thanh Thieu

Maven at MEDIQA-CORR 2024: Leveraging RAG and Medical LLM for Error Detection and Correction in Medical Notes

Suramya Jadhav, Abhay Shanbhag, Sumedh Joshi, Atharva Date, Sheetal Sonawane

PromptMind Team at MEDIQA-CORR 2024: Improving Clinical Text Correction with Error Categorization and LLM Ensembles

Satya Gundabathula, Sriram Kolar

PromptMind Team at EHRSQL-2024: Improving Reliability of SQL Generation using Ensemble LLMs

Satya Gundabathula, Sriram Kolar

KnowLab_AIMed at MEDIQA-CORR 2024: Chain-of-Though (CoT) prompting strategies for medical error detection and correction

Zhaolong Wu, Abul Hasan, Jinge Wu, Yunsoo Kim, Jason Cheung

MediFact at MEDIQA-CORR 2024: Why AI Needs a Human Touch

Nadia Saeed

MediFact at MEDIQA-M3G 2024: Medical Question Answering in Dermatology with Multimodal Learning

Nadia Saeed

TEAM MIPAL at MEDIQA-M3G 2024: Large VQA Models for Dermatological Diagnosis

Hyeonjin Kim, Min Kim, Jae Jang, KiYoon Yoo, Nojun Kwak

Semi-automatic Construction of a Word Complexity Lexicon for Japanese Medical Terminology

Soichiro Sugihara, Tomoyuki Kajiwara, Takashi Ninomiya, Shoko Wakamiya, Eiji Aramaki

Evaluating Lexicon Incorporation for Depression Symptom Estimation

Kirill Milintsevich, Gaël Dias, Kairit Sirts

Context Aggregation with Topic-focused Summarization for Personalized Medical Dialogue Generation

Zhengyuan Liu, Siti Salleh, Pavitra Krishnaswamy, Nancy Chen

Leveraging Prompt-Learning for Structured Information Extraction from Crohn’s Disease Radiology Reports in a Low-Resource Language

Liam Hazan, Naama Gavrielov, Roi Reichart, Talar Hagopian, Mary-Louise Greer

ERD: A Framework for Improving LLM Reasoning for Cognitive Distortion Classification

Sehee Lim, Yejin Kim, Chi-Hyun Choi, Jy-yong Sohn, Byung-Hoon Kim

SERPENT-VLM : Self-Refining Radiology Report Generation Using Vision Language Models

Manav Kapadnis, Sohan Patnaik, Abhilash Nandy, Sourjyadip Ray, Pawan Goyal

Adapting Abstract Meaning Representation Parsing to the Clinical Narrative – the SPRING THYME parser

Jon Cai, Kristin Wright-Bettner, Martha Palmer, Guergana Savova, James Martin

LLM-Based Section Identifiers Excel on Open Source but Stumble in Real World Applications

Saranya Krishnamoorthy, Ayush Singh, Shabnam Tafreshi

Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering

Cuong Ha, Shima Asaadi, Sanjeev Kumar Karn, Oladimeji Farri, Tobias Heimann

Leveraging pre-trained large language models for aphasia detection in English and Chinese speakers

Yan Cong, Jiyeon Lee, Arianna LaCroix

Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain

Burcu Sayin, Pasquale Minervini, Jacopo Staiano, Andrea Passerini

Revisiting Clinical Outcome Prediction for MIMIC-IV

Tom Röhr, Alexei Figueroa, Jens-Michalis Papaioannou, Conor Fallon, Keno Bressem

Leveraging Wikidata for Biomedical Entity Linking in a Low-Resource Setting: A Case Study for German

Faizan E Mustafa, Corina Dima, Juan Ochoa, Steffen Staab

Conversational Topic Recommendation in Counseling and Psychotherapy with Decision Transformer and Large Language Models

Aylin Gunal, Baihan Lin, Djallel Bouneffouf

Large Language Models Provide Human-Level Medical Text Snippet Labeling

Ibtihel Amara, Haiyang Yu, Fan Zhang, Yuchen Liu, Benny Li

Using Structured Health Information for Controlled Generation of Clinical Cases in French

Hugo Boulanger, Nicolas Hiebel, Olivier Ferret, Karën Fort, Aurélie Névéol

LlamaMTS: Optimizing Metastasis Detection with Llama Instruction Tuning and BERT-Based Ensemble in Italian Clinical Reports

Livia Lilli, Stefano Patarnello, Carlotta Masciocchi, Valeria Masiello, Fabio Marazzi

DERA: Enhancing Large Language Model Completions with Dialog-Enabled Resolving Agents

Varun Nair, Elliot Schumacher, Geoffrey Tso, Anitha Kannan

A Privacy-Preserving Corpus for Occupational Health in Spanish: Evaluation for NER and Classification Tasks

Claudio Aracena, Luis Miranda, Thomas Vakili, Fabián Villena, Tamara Quiroga

A Multilevel Analysis of PubMed-only BERT-based Biomedical Models

Vicente Sanchez Carmona, Shanshan Jiang, Bin Dong

Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain

Aryo Gema, Pasquale Minervini, Luke Daines, Tom Hope, Beatrice Alex

DAIC-WOZ: On the Validity of Using the Therapist’s prompts in Automatic Depression Detection from Clinical Interviews

Sergio Burdisso, Ernesto Reyes-Ramírez, Esau Villatoro-tello, Fernando Sanchez-Vega, Adrian Lopez Monroy

Building A German Clinical Named Entity Recognition System without In-domain Training Data

Siting Liang, Daniel Sonntag

Working Alliance Transformer for Psychotherapy Dialogue Classification

Baihan Lin, Guillermo Cecchi, Djallel Bouneffouf

ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes

Zhichao Yang, Avijit Mitra, Sunjae Kwon, Hong Yu

Retrieval augmented text-to-SQL generation for epidemiological question answering using electronic health records

Angelo Ziletti, Leonardo DAmbrosi

Gemini Goes to Med School: Exploring the Capabilities of Multimodal Large Language Models on Medical Challenge Problems & Hallucinations

Ankit Pal, Malaikannan Sankarasubbu

Efficient Medical Question Answering with Knowledge-Augmented Question Generation

Julien Khlaut, Corentin Dancette, Elodie Ferreres, Alaedine Bennani, Paul Hérent

Exploring Robustness in Doctor-Patient Conversation Summarization: An Analysis of Out-of-Domain SOAP Notes

Yu-Wen Chen, Julia Hirschberg

ITEC at MLSP 2024: Transferring Predictions of Lexical Difficulty from Non-Native Readers

Anaïs Tack

GMU at MLSP 2024: Multilingual Lexical Simplification with Transformer Models

Dhiman Goswami, Kai North, Marcos Zampieri

RETUYT-INCO at MLSP 2024: Experiments on Language Simplification using Embeddings, Classifiers and Large Language Models

Ignacio Sastre, Leandro Alfonso, Facundo Fleitas, Federico Gil, Andrés Lucas

Archaeology at MLSP 2024: Machine Translation for Lexical Complexity Prediction and Lexical Simplification

Petru Cristea, Sergiu Nisioi

ISEP_Presidency_University at MLSP 2024 Shared Task: Using GPT-3.5 to Generate Substitutes for Lexical Simplification

Benjamin Dutilleul, Mathis Debaillon, Sandeep Mathias

ANU at MLSP-2024: Prompt-based Lexical Simplification for English and Sinhala

Sandaru Seneviratne, Hanna Suominen

TMU-HIT at MLSP 2024: How Well Can GPT-4 Tackle Multilingual Lexical Simplification?

Taisei Enomoto, Hwichan Kim, Tosho Hirasawa, Yoshinari Nagai, Ayako Sato

The BEA 2024 Shared Task on the Multilingual Lexical Simplification Pipeline

Matthew Shardlow, Fernando Alva-Manchego, Riza Batista-Navarro, Stefan Bott, Saul Calderon Ramirez

UNED team at BEA 2024 Shared Task: Testing different Input Formats for predicting Item Difficulty and Response Time in Medical Exams

Alvaro Rodrigo, Sergio Moreno-Álvarez, Anselmo Peñas

Large Language Model-based Pipeline for Item Difficulty and Response Time Estimation for Educational Assessments

Hariram Veeramani, Surendrabikram Thapa, Natarajan Balaji Shankar, Abeer Alwan

Using Machine Learning to Predict Item Difficulty and Response Time in Medical Tests

Mehrdad Yousefpoori-Naeim, Shayan Zargari, Zahra Hatami

UPN-ICC at BEA 2024 Shared Task: Leveraging LLMs for Multiple-Choice Questions Difficulty Prediction

George Duenas, Sergio Jiménez, Geral Mateus Ferro

Leveraging Physical and Semantic Features of text item for Difficulty and Response Time Prediction of USMLE Questions

Gummuluri Venkata Ravi Ram, Ashinee Kesanam, Anand Kumar M

Utilizing Machine Learning to Predict Question Difficulty and Response Time for Enhanced Test Construction

Rishikesh Fulari, Jonathan Rusert

Item Difficulty and Response Time Prediction with Large Language Models: An Empirical Analysis of USMLE Items

Okan Bulut, Guher Gorgun, Bin Tan

ITEC at BEA 2024 Shared Task: Predicting Difficulty and Response Time of Medical Exam Questions with Statistical, Machine Learning, and Language Models

Anaïs Tack, Siem Buseyne, Changsheng Chen, Robbe D’hondt, Michiel De Vrindt

The British Council submission to the BEA 2024 shared task

Mariano Felice, Zeynep Duran Karaoz

UnibucLLM: Harnessing LLMs for Automated Prediction of Item Difficulty and Response Time for Multiple-Choice Questions

Ana-Cristina Rogoz, Radu Tudor Ionescu

Predicting Item Difficulty and Item Response Time with Scalar-mixed Transformer Encoder Models and Rational Network Regression Heads

Sebastian Gombert, Lukas Menzel, Daniele Di Mitri, Hendrik Drachsler

Findings from the First Shared Task on Automated Prediction of Difficulty and Response Time for Multiple-Choice Questions

Victoria Yaneva, Kai North, Peter Baldwin, Le An Ha, Saed Rezayi

From Miscue to Evidence of Difficulty: Analysis of Automatically Detected Miscues in Oral Reading for Feedback Potential

Beata Beigman Klebanov, Michael Suhan, Tenaha O’reilly, Zuowei Wang

Building Robust Content Scoring Models for Student Explanations of Social Justice Science Issues

Allison Bradford, Kenneth Steimel, Brian Riordan, Marcia Linn

Transfer Learning of Argument Mining in Student Essays

Yuning Ding, Julian Lohmann, Nils-Jonathan Schaller, Thorben Jansen, Andrea Horbach

BERT-IRT: Accelerating Item Piloting with BERT Embeddings and Explainable IRT Models

Kevin P. Yancey, Andrew Runge, Geoffrey Laflair, Phoebe Mulcaire

Harnessing GPT to Study Second Language Learner Essays: Can We Use Perplexity to Determine Linguistic Competence?

Ricardo Muñoz Sánchez, Simon Dobnik, Elena Volodina

Assessing Student Explanations with Large Language Models Using Fine-Tuning and Few-Shot Learning

Dan Carpenter, Wookhee Min, Seung Lee, Gamze Ozogul, Xiaoying Zheng

Anna Karenina Strikes Again: Pre-Trained LLM Embeddings May Favor High-Performing Learners

Abigail Gurin Schleifer, Beata Beigman Klebanov, Moriah Ariely, Giora Alexandron

Automatic Crossword Clues Extraction for Language Learning

Santiago Berruti, Arturo Collazo, Diego Sellanes, Aiala Rosá, Luis Chiruzzo

Using Large Language Models to Assess Young Students’ Writing Revisions

Tianwen Li, Zhexiong Liu, Lindsay Matsumura, Elaine Wang, Diane Litman

Automated Sentence Generation for a Spaced Repetition Software

Benjamin Paddags, Daniel Hershcovich, Valkyrie Savage

Improving Readability Assessment with Ordinal Log-Loss

Ho Hung Lim, John Lee

Error Tracing in Programming: A Path to Personalised Feedback

Martha Shaka, Diego Carraro, Kenneth Brown

Automated Essay Scoring Using Grammatical Variety and Errors with Multi-Task Learning and Item Response Theory

Kosuke Doi, Katsuhito Sudoh, Satoshi Nakamura

LLMs in Short Answer Scoring: Limitations and Promise of Zero-Shot and Few-Shot Approaches

Imran Chamieh, Torsten Zesch, Klaus Giebermann

Towards Fine-Grained Pedagogical Control over English Grammar Complexity in Educational Text Generation

Dominik Glandorf, Detmar Meurers

Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation

Maja Stahl, Leon Biermann, Andreas Nehring, Henning Wachsmuth

Evaluating Vocabulary Usage in LLMs

Matthew Durward, Christopher Thomson

Towards Automated Document Revision: Grammatical Error Correction, Fluency Edits, and Beyond

Masato Mita, Keisuke Sakaguchi, Masato Hagiwara, Tomoya Mizumoto, Jun Suzuki

Identifying Fairness Issues in Automatically Generated Testing Content

Kevin Stowe, Benny Longwill, Alyssa Francis, Tatsuya Aoyama, Debanjan Ghosh

Improving Automated Distractor Generation for Math Multiple-choice Questions with Overgenerate-and-rank

Alexander Scarlatos, Wanyong Feng, Digory Smith, Simon Woodhead, Andrew Lan

Fairness in Automated Essay Scoring: A Comparative Analysis of Algorithms on German Learner Essays from Secondary Education

Nils-Jonathan Schaller, Yuning Ding, Andrea Horbach, Jennifer Meyer, Thorben Jansen

Explainable AI in Language Learning: Linking Empirical Evidence and Theoretical Concepts in Proficiency and Readability Modeling of Portuguese

Luisa Ribeiro-Flucht, Xiaobin Chen, Detmar Meurers

Automated Evaluation of Teacher Encouragement of Student-to-Student Interactions in a Simulated Classroom Discussion

Michael Ilagan, Beata Beigman Klebanov, Jamie Mikeska

Using Program Repair as a Proxy for Language Models’ Feedback Ability in Programming Education

Charles Koutcheme, Nicola Dainese, Arto Hellas

Can GPT-4 do L2 analytic assessment?

Stefano Bannò, Hari K. Vydana, Kate M. Knill, Mark J. F. Gales

Improving Transfer Learning for Early Forecasting of Academic Performance by Contextualizing Language Models

Ahatsham Hayat, Bilal Khan, Mohammad Hasan

Predicting Initial Essay Quality Scores to Increase the Efficiency of Comparative Judgment Assessments

Michiel De Vrindt, Anaïs Tack, Renske Bouwer, Wim Van Den Noortgate, Marije Lesterhuis

Scoring with Confidence? – Exploring High-confidence Scoring for Saving Manual Grading Effort

Marie Bexte, Andrea Horbach, Lena Schützler, Oliver Christ, Torsten Zesch

Improving Socratic Question Generation using Data Augmentation and Preference Optimization

Nischal Ashok Kumar, Andrew Lan

A World CLASSE Student Summary Corpus

Scott Crossley, Perpetual Baffour, Mihai Dascalu, Stefan Ruseti

Automated Scoring of Clinical Patient Notes: Findings From the Kaggle Competition and Their Translation into Practice

Victoria Yaneva, King Yiu Suen, Le An Ha, Janet Mee, Milton Quranda

Can Language Models Guess Your Identity? Analyzing Demographic Biases in AI Essay Scoring

Alexander Kwako, Christopher Ormerod

Large Language Models Are State-of-the-Art Evaluator for Grammatical Error Correction

Masamune Kobayashi, Masato Mita, Mamoru Komachi

Beyond Flesch-Kincaid: Prompt-based Metrics Improve Difficulty Classification of Educational Texts

Donya Rooein, Paul Röttger, Anastassia Shaitarova, Dirk Hovy

Using Adaptive Empathetic Responses for Teaching English

Li Siyan, Teresa Shao, Julia Hirschberg, Zhou Yu

Pillars of Grammatical Error Correction: Comprehensive Inspection Of Contemporary Approaches In The Era of Large Language Models

Kostiantyn Omelianchuk, Andrii Liubonko, Oleksandr Skurzhanskyi, Artem Chernodub, Oleksandr Korniienko

Synthetic Data Generation for Low-resource Grammatical Error Correction with Tagged Corruption Models

Felix Stahlberg, Shankar Kumar

How Good are Modern LLMs in Generating Relevant and High-Quality Questions at Different Bloom’s Skill Levels for Indian High School Social Science Curriculum?

Nicy Scaria, Suma Dharani Chenna, Deepak Subramani

Findings of the AmericasNLP 2024 Shared Task on Machine Translation into Indigenous Languages

Abteen Ebrahimi, Ona de Gibert, Raúl Vázquez, Rolando Coto-Solano, Pavel Denisov

Findings of the AmericasNLP 2024 Shared Task on the Creation of Educational Materials for Indigenous Languages

Luis Chiruzzo, Pavel Denisov, Alejandro Molina-Villegas, Silvia Fernandez-Sabido, Rolando Coto-Solano

The role of morphosyntactic similarity in generating related sentences

Michael Hammond

Exploring Very Low-Resource Translation with LLMs: The University of Edinburgh’s Submission to AmericasNLP 2024 Translation Task

Vivek Iyer, Bhavitvya Malik, Wenhao Zhu, Pavel Stepachev, Pinzhen Chen