EMNLP
Collection
Accepted papers for EMNLP (Conference on Empirical Methods in Natural Language Processing), one dataset per year. • 13 items • Updated
title stringlengths 16 168 | paper_url stringlengths 43 46 | authors listlengths 1 32 | abstract large_stringlengths 346 1.96k | anthology_id stringlengths 17 20 | doi stringlengths 29 32 | award stringclasses 7
values | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
values | embedding listlengths 768 768 |
|---|---|---|---|---|---|---|---|---|---|
Towards Automated Error Discovery: A Study in Conversational AI | https://aclanthology.org/2025.emnlp-main.1/ | [
"Dominic Petrak",
"Thy Thy Tran",
"Iryna Gurevych"
] | Although LLM-based conversational agents demonstrate strong fluency and coherence, they still produce undesirable behaviors (errors) that are challenging to prevent from reaching users during deployment. Recent research leverages large language models (LLMs) to detect errors and guide response-generation models toward ... | 2025.emnlp-main.1 | 10.18653/v1/2025.emnlp-main.1 | null | 2509.10833 | title_snapshot | [
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Break the Checkbox: Challenging Closed-Style Evaluations of Cultural Alignment in LLMs | https://aclanthology.org/2025.emnlp-main.2/ | [
"Mohsinul Kabir",
"Ajwad Abrar",
"Sophia Ananiadou"
] | A large number of studies rely on closed-style multiple-choice surveys to evaluate cultural alignment in Large Language Models (LLMs). In this work, we challenge this constrained evaluation paradigm and explore more realistic, unconstrained approaches. Using the World Values Survey (WVS) and Hofstede Cultural Dimension... | 2025.emnlp-main.2 | 10.18653/v1/2025.emnlp-main.2 | null | 2502.08045 | title_snapshot | [
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Biased Tales: Cultural and Topic Bias in Generating Children’s Stories | https://aclanthology.org/2025.emnlp-main.3/ | [
"Donya Rooein",
"Vilém Zouhar",
"Debora Nozza",
"Dirk Hovy"
] | Stories play a pivotal role in human communication, shaping beliefs and morals, particularly in children. As parents increasingly rely on large language models (LLMs) to craft bedtime stories, the presence of cultural and gender stereotypes in these narratives raises significant concerns. To address this issue, we pres... | 2025.emnlp-main.3 | 10.18653/v1/2025.emnlp-main.3 | null | 2509.07908 | title_snapshot | [
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Large Language Models as Realistic Microservice Trace Generators | https://aclanthology.org/2025.emnlp-main.4/ | [
"Donghyun Kim",
"Sriram Ravula",
"Taemin Ha",
"Alex Dimakis",
"Daehyeok Kim",
"Aditya Akella"
] | Workload traces are essential to understand complex computer systems’ behavior and manage processing and memory resources. Since real-world traces are hard to obtain, synthetic trace generation is a promising alternative. This paper proposes a first-of-a-kind approach that relies on training a large language model (LLM... | 2025.emnlp-main.4 | 10.18653/v1/2025.emnlp-main.4 | null | 2502.17439 | title_snapshot | [
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JUDGEBERT: Assessing Legal Meaning Preservation Between Sentences | https://aclanthology.org/2025.emnlp-main.5/ | [
"David Beauchemin",
"Michelle Albert-Rochette",
"Richard Khoury",
"Pierre-Luc Déziel"
] | Simplifying text while preserving its meaning is a complex yet essential task, especially in sensitive domain applications like legal texts. When applied to a specialized field, like the legal domain, preservation differs significantly from its role in regular texts. This paper introduces FrJUDGE, a new dataset to asse... | 2025.emnlp-main.5 | 10.18653/v1/2025.emnlp-main.5 | null | 2508.16870 | title_snapshot | [
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QFrCoLA: a Quebec-French Corpus of Linguistic Acceptability Judgments | https://aclanthology.org/2025.emnlp-main.6/ | [
"David Beauchemin",
"Richard Khoury"
] | Large and Transformer-based language models perform outstandingly in various downstream tasks. However, there is limited understanding regarding how these models internalize linguistic knowledge, so various linguistic benchmarks have recently been proposed to facilitate syntactic evaluation of language models across la... | 2025.emnlp-main.6 | 10.18653/v1/2025.emnlp-main.6 | null | 2508.16867 | title_snapshot | [
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Revisiting LLM Value Probing Strategies: Are They Robust and Expressive? | https://aclanthology.org/2025.emnlp-main.7/ | [
"Siqi Shen",
"Mehar Singh",
"Lajanugen Logeswaran",
"Moontae Lee",
"Honglak Lee",
"Rada Mihalcea"
] | The value orientation of Large Language Models (LLMs) has been extensively studied, as it can shape user experiences across demographic groups.However, two key challenges remain: (1) the lack of systematic comparison across value probing strategies, despite the Multiple Choice Question (MCQ) setting being vulnerable to... | 2025.emnlp-main.7 | 10.18653/v1/2025.emnlp-main.7 | null | 2507.13490 | title_snapshot | [
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A Systematic Analysis of Base Model Choice for Reward Modeling | https://aclanthology.org/2025.emnlp-main.8/ | [
"Kian Ahrabian",
"Pegah Jandaghi",
"Negar Mokhberian",
"Sai Praneeth Karimireddy",
"Jay Pujara"
] | Reinforcement learning from human feedback (RLHF) and, at its core, reward modeling have become a crucial part of training powerful large language models (LLMs). One commonly overlooked factor in training high-quality reward models (RMs) is the effect of the base model, which is becoming more challenging to choose give... | 2025.emnlp-main.8 | 10.18653/v1/2025.emnlp-main.8 | null | 2505.10775 | title_snapshot | [
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Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance | https://aclanthology.org/2025.emnlp-main.9/ | [
"Branislav Pecher",
"Ivan Srba",
"Maria Bielikova"
] | When solving NLP tasks with limited labelled data, researchers typically either use a general large language model without further update, or use a small number of labelled samples to tune a specialised smaller model. In this work, we answer an important question – how many labelled samples are required for the special... | 2025.emnlp-main.9 | 10.18653/v1/2025.emnlp-main.9 | null | 2402.12819 | title_snapshot | [
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Is the Top Still Spinning? Evaluating Subjectivity in Narrative Understanding | https://aclanthology.org/2025.emnlp-main.10/ | [
"Melanie Subbiah",
"Akankshya Mishra",
"Grace Kim",
"Liyan Tang",
"Greg Durrett",
"Kathleen McKeown"
] | Determining faithfulness of a claim to a source document is an important problem across many domains. This task is generally treated as a binary judgment of whether the claim is supported or unsupported in relation to the source. In many cases, though, whether a claim is supported can be ambiguous. For instance, it may... | 2025.emnlp-main.10 | 10.18653/v1/2025.emnlp-main.10 | null | 2504.01132 | title_snapshot | [
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... |
MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors | https://aclanthology.org/2025.emnlp-main.11/ | [
"Jakub Macina",
"Nico Daheim",
"Ido Hakimi",
"Manu Kapur",
"Iryna Gurevych",
"Mrinmaya Sachan"
] | Evaluating the pedagogical capabilities of AI-based tutoring models is critical for making guided progress in the field. Yet, we lack a reliable, easy-to-use, and simple-to-run evaluation that reflects the pedagogical abilities of models. To fill this gap, we present MathTutorBench, an open-source benchmark for holisti... | 2025.emnlp-main.11 | 10.18653/v1/2025.emnlp-main.11 | null | 2502.18940 | title_snapshot | [
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