Papers with MIT
BERTweet: A pre-trained language model for English Tweets (2020.emnlp-demos)
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| Challenge: | Experiments show that BERTweet outperforms strong baselines RoBERTa-base and XLM-R-base on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification. |
| Approach: | They propose to train a pre-trained language model for English Tweets using the RoBERTa pre training procedure and use it to train the model. |
| Outcome: | Experiments show that the model outperforms baseline models on three Tweet NLP tasks: Part-of-speech tagging, Named-entity recognition and text classification. |
Web-based Annotation Interface for Derivational Morphology (2022.naacl-demo)
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| Challenge: | a visual interface for manual annotation of language resources for derivational morphology is created using relatively simple programming techniques. |
| Approach: | They propose a web-based visual interface for manual annotation of language resources for derivational morphology. |
| Outcome: | The proposed interface can be used for manual annotation of derivational morphology resources. |
NLP Workbench: Efficient and Extensible Integration of State-of-the-art Text Mining Tools (2023.eacl-demo)
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| Challenge: | NLP Workbench is a web-based text mining platform that allows non-expert users to obtain semantic understanding of large-scale corpora using state-of-the-art text mining models. |
| Approach: | They propose to use a microservice architecture to replace existing models or integrate a new one. |
| Outcome: | The proposed model is extensible and can be easily replaced or integrated with existing models. |
BME-UW at SRST-2019: Surface realization with Interpreted Regular Tree Grammars (D19-63)
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| Challenge: | adaamko's system restores word order and inflection from a graph of typed, directed dependencies between lemmas. |
| Approach: | They propose a method that restores word order and inflection from a graph of typed, directed dependencies between lemmas. |
| Outcome: | The proposed system restores word order and inflection from a graph of typed, directed dependencies between lemmas. |
TransIns: Document Translation with Markup Reinsertion (2021.emnlp-demo)
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| Challenge: | MT models cannot translate complex formatted documents, as markup can be nested, apply to spans contiguous in source but non-contiguous. |
| Approach: | They propose a system for non-plain text document translation that reinserts markup into translated sentences using token alignments between source and target sentences. |
| Outcome: | The proposed system outperforms translation services in terms of markup quality . it integrates token alignments between source and target sentences to reinsert markup . the proposed system is available under the MIT license . |
Loki: An Open-Source Tool for Fact Verification (2025.coling-demos)
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Haonan Li, Xudong Han, Hao Wang, Yuxia Wang, Minghan Wang, Rui Xing, Yilin Geng, Zenan Zhai, Preslav Nakov, Timothy Baldwin
| Challenge: | Loki is an open-source fact-checking tool designed to address the growing problem of misinformation. |
| Approach: | They propose a tool that breaks down the fact-checking task into five steps . they propose LOKI, which offers a semiautomated, human-in-the-loop approach . |
| Outcome: | a new open-source tool is designed to address the growing problem of misinformation . the tool breaks down the fact-checking task into five steps to assist human judgment . |
Small-Text: Active Learning for Text Classification in Python (2023.eacl-demo)
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| Challenge: | small-text is an easy-to-use active learning library for text classification . it features a variety of pre-implemented state-of-the-art query strategies and stopping criteria . |
| Approach: | They introduce small-text, an easy-to-use active learning library for Python . it offers pool-based active learning for single- and multi-label text classification . they find it matches vanilla transformer fine-tuning in terms of classification accuracy . |
| Outcome: | The proposed library outperforms vanilla transformer fine-tuning in classification accuracy and area under the curve. |
ReDel: A Toolkit for LLM-Powered Recursive Multi-Agent Systems (2024.emnlp-demo)
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| Challenge: | Recent studies show that large language models can be used to construct complex multi-agent systems. |
| Approach: | They propose a toolkit for recursive multi-agent systems that supports custom tool-use, delegation schemes, event-based logging, and interactive replay. |
| Outcome: | The proposed tool achieves significant performance gains on agentic benchmarks and identify potential areas of improvement through visualization and debugging tools. |
stopes - Modular Machine Translation Pipelines (2022.emnlp-demos)
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Pierre Andrews, Guillaume Wenzek, Kevin Heffernan, Onur Çelebi, Anna Sun, Ammar Kamran, Yingzhe Guo, Alexandre Mourachko, Holger Schwenk, Angela Fan
| Challenge: | Neural machine translation is a natural language deep learning application that needs data to be trained. |
| Approach: | They describe a framework that empowers scalability and versatility for research use cases. |
| Outcome: | The proposed framework empowers scalability and versatility for research use cases. |
Hindsight: Structured Agent Memory that Retains, Recalls, and Reflects (2026.acl-demo)
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Christopher Latimer, Nicolò Boschi, Andrew Neeser, Chris Bartholomew, Gaurav Srivastava, Xuan Wang, Naren Ramakrishnan
| Challenge: | Hindsight organizes long-term memory into four logical networks and exposes three core operations. |
| Approach: | Hindsight organizes long-term memory into four logical networks and exposes three core operations. |
| Outcome: | Hindsight is a working memory system for AI agents that separates facts from beliefs . the system outperforms existing models on LongMemEval and LoCoMo with 83.6% accuracy . |
ExplainaBoard: An Explainable Leaderboard for NLP (2021.acl-demo)
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Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaichen Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, Graham Neubig
| Challenge: | Using leaderboards, researchers can track the performance of various systems on various NLP tasks. |
| Approach: | They propose a new conceptualization and implementation of NLP evaluation using a leaderboard. |
| Outcome: | The ExplainaBoard is an evaluation tool for natural language processing (NLP) it covers more than 400 systems, 50 datasets, 40 languages, and 12 tasks. |
MASEval: Extending Multi-Agent Evaluation from Models to Systems (2026.acl-demo)
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Cornelius Emde, Alexander Rubinstein, Anmol Goel, Ahmed Heakl, Sangdoo Yun, Seong Joon Oh, Martin Gubri
| Challenge: | MASEval provides a framework-agnostic, system-level comparison across any agent framework and benchmark. |
| Approach: | They propose a Python library that treats the entire agentic system as the unit of analysis. |
| Outcome: | The proposed framework treats the entire agentic system as the unit of analysis. |
TokCollate: A Comprehensive Tool for Tokenizer Evaluation and Visualization across Languages (2026.acl-demo)
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| Challenge: | Tokenization quality varies significantly across languages, leading to disparities in LLM performance and cost for speakers of less-resourced languages. |
| Approach: | They propose a Python-based evaluation framework and a JavaScript visualization interface that evaluates tokenizers in a variety of languages. |
| Outcome: | TokCollate is an evaluation framework for tokenizers with a JavaScript visualization interface. |
ALToolbox: A Set of Tools for Active Learning Annotation of Natural Language Texts (2022.emnlp-demos)
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Akim Tsvigun, Leonid Sanochkin, Daniil Larionov, Gleb Kuzmin, Artem Vazhentsev, Ivan Lazichny, Nikita Khromov, Danil Kireev, Aleksandr Rubashevskii, Olga Shahmatova, Dmitry V. Dylov, Igor Galitskiy, Artem Shelmanov
| Challenge: | Currently, the framework supports text classification, sequence tagging, and seq2seq tasks. |
| Approach: | They propose an open-source framework for active learning annotation in natural language processing that provides an easy-to-deploy GUI annotation tool directly in the Jupyter IDE. |
| Outcome: | The proposed framework reduces computational overhead and duration of AL iterations and increases annotated data reusability. |
gec-metrics: A Unified Library for Grammatical Error Correction Evaluation (2025.acl-demo)
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| Challenge: | a library for using and developing grammatical error correction (GEC) evaluation metrics is released under the MIT license . |
| Approach: | They propose a library for using and developing grammatical error correction (GEC) evaluation metrics through a unified interface. |
| Outcome: | The proposed method is based on a unified evaluation framework with a strong focus on API usage and extensible. |
KWJA: A Unified Japanese Analyzer Based on Foundation Models (2023.acl-demo)
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Nobuhiro Ueda, Kazumasa Omura, Takashi Kodama, Hirokazu Kiyomaru, Yugo Murawaki, Daisuke Kawahara, Sadao Kurohashi
| Challenge: | KWJA supports a wide range of tasks including typo correction, word segmentation, word normalization, named entity recognition, dependency parsing, PAS analysis, bridging reference resolution, coreference resolution, and discourse relation analysis. |
| Approach: | They propose to build a Japanese text analyzer based on foundation models that performs a wide range of tasks. |
| Outcome: | The proposed model performs better in a multi-task manner than other analyzers with specialized models. |
The Dangers of Indirect Prompt Injection Attacks on LLM-based Autonomous Web Navigation Agents: A Demonstration (2025.emnlp-demos)
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| Challenge: | Large Language Model (LLM)-integrated applications are becoming more popular to support, augment, and automate tasks. |
| Approach: | They propose to embed universal adversarial triggers in webpage HTML to hijack agents . they also use a browser-gym agent powered by Llama-3.1 to test their system . |
| Outcome: | The proposed system software is released under the MIT License . |
ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning (2026.acl-demo)
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Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, Minh Ngoc Ta, Ekaterina Fadeeva, Artem Vazhentsev, Daria Galimzianova, Nikolai Rozanov, Viktor Mazanov, Jingwei Ni, Tianyi Wu, Igor Kiselev, Mrinmaya Sachan, Iryna Gurevych, Preslav Nakov, Timothy Baldwin, Artem Shelmanov
| Challenge: | Existing TTC scaling strategies and reasoning scorers are fragmented and evaluated under inconsistent protocols. |
| Approach: | They propose a framework for seamless test-time compute scaling of large language model reasoning . they use a modular Python library to implement state-of-the-art scaling strategy and scorer families . |
| Outcome: | The proposed framework evaluates performance and computational efficiency on mathematical and coding tasks. |
Template-Based Named Entity Recognition Using BART (2021.findings-acl)
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| Challenge: | Existing methods for fewshot NER do not make full use of knowledge transfer in NER model parameters. |
| Approach: | They propose a template-based method for NER that treats NER as a language model ranking problem in a sequence-to-sequence framework. |
| Outcome: | The proposed method achieves 92.55% F1 score on the CoNLL03 task and significantly better than fine-tuning BERT 10.88%, 15.34%, and 11.73% F1 scores on the MIT Movie, the ATIS, and the MATLAB task. |
LMUNIT: Fine-grained Evaluation with Natural Language Unit Tests (2025.findings-emnlp)
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Jon Saad-Falcon, Rajan Pathe Vivek, William Berrios, Nandita Shankar Naik, Matija Franklin, Bertie Vidgen, Amanpreet Singh, Douwe Kiela, Shikib Mehri
| Challenge: | Using natural language unit tests, language models are costly and noisy, and automated metrics provide only coarse, difficult-to-interpret signals. |
| Approach: | They propose a paradigm that decomposes response quality into explicit, testable criteria and a unified scoring model, LMUnit, which combines multi-objective training across preferences, direct ratings, and natural language rationales. |
| Outcome: | The proposed paradigm significantly improves inter-annotator agreement and enables more effective LLM development workflows. |
Multilingual Open Text Release 1: Public Domain News in 44 Languages (2022.lrec-1)
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| Challenge: | a corpus of permissively licensed text is being developed in 44 languages, many of which have limited existing text resources for natural language processing. |
| Approach: | They propose to create a multilingual corpus containing text in 44 languages . they describe their process for collecting, filtering, and processing the data . |
| Outcome: | The first release of the corpus contains over 2.8 million news articles and an additional 1 million short snippets published between 2001–2022 and collected from Voice of America news websites. |
ReCoT-NER: Enhancing Zero-Shot Named Entity Recognition through Chain-of-Thought Prompting and Recall-Oriented Loss Optimization (2026.findings-acl)
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| Challenge: | Named Entity Recognition (NER) is a key component of natural language processing (NLP) but it is difficult to implement in specialized domains such as wind power fault diagnosis. |
| Approach: | They propose a reasoning-enhanced generative framework that integrates Chain-of-Thought prompting and recall-oriented loss optimization to address these challenges. |
| Outcome: | The proposed framework improves recall and overall F1 performance across general and industrial domains. |
CILex: An Investigation of Context Information for Lexical Substitution Methods (2022.coling-1)
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| Challenge: | Existing methods for lexical substitution rely on manually curated lexicals and contextual word embedding models. |
| Approach: | They propose a method that uses contextual sentence embeddings to generate substitutes for a target word given a context and a model that captures additional context information complimenting contextual word embedders. |
| Outcome: | The proposed method is state-of-the-art on the widely used LS07 and CoInCo datasets with P@1 scores of 55.96% and 57.25% for lexical substitution. |
Primus: A Pioneering Collection of Open-Source Datasets for Cybersecurity LLM Training (2025.emnlp-main)
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| Challenge: | Large Language Models (LLMs) have shown remarkable advancements in specialized fields such as finance, law, and medicine. |
| Approach: | They propose to provide datasets covering all major training stages including pretraining, instruction fine-tuning, and reasoning distillation with cybersecurity-specific self-reflection data. |
| Outcome: | Extensive ablation studies show that LLMs acquire their knowledge during pretraining, while reasoning distillation leads to a 15% gain in security certification (CISSP). |
Web-based Annotation Tool for Inflectional Language Resources (L18-1)
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| Challenge: | Wasim is a web-based tool for semi-automatic morphosyntactic annotation of inflectional languages. |
| Approach: | They present a web-based tool for semi-automatic morphosyntactic annotation of inflectional languages resources. |
| Outcome: | The tool has high flexibility in segmenting tokens, editing, diacritizing, labelling tokens and segments. |
A New Aligned Simple German Corpus (2023.acl-long)
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| Challenge: | “Leichte Sprache” is a regulated language aimed to facilitate complex written language that would otherwise stay inaccessible to different groups of people. |
| Approach: | They propose to use automatic sentence-alignment methods to align multiple document-aligned sources to improve their sentence alignments. |
| Outcome: | The proposed dataset outperforms previous work and is available under MIT license. |
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation (2024.emnlp-main)
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| Challenge: | Sentence segmentation is a key task in many NLP systems, but no prior method has achieved all of the features needed to segment a text into sentences. |
| Approach: | They propose a new model that uses punctuation to enhance robustness and adaptability. |
| Outcome: | The proposed model outperforms baselines across 8 corpora across diverse domains and languages and is available under the MIT license. |
Gramble: A Tabular Programming Language for Collaborative Linguistic Modeling (2024.lrec-main)
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| Challenge: | a new programming language for linguistic parsing and generation is available for free . a cross-platform interpreter is available on the web via google sheets . |
| Approach: | a new Gramble programming language is being developed for linguistic parsing and generation . the language is a domain-specific programming language that supports live group programming . a cross-platform interpreter is available for Windows, MacOS, and UNIX . |
| Outcome: | a new programming language for linguistic parsing and generation is released under the MIT license . the language is based on handwritten declarative code rather than machine learning . |
TopicNet: Making Additive Regularisation for Topic Modelling Accessible (2020.lrec-1)
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Victor Bulatov, Vasiliy Alekseev, Konstantin Vorontsov, Darya Polyudova, Eugenia Veselova, Alexey Goncharov, Evgeny Egorov
| Challenge: | TopicNet is a Python module for topic modeling. |
| Approach: | They introduce a Python module for topic modeling that brings regularization topic modeling to non-specialists using a general-purpose language. |
| Outcome: | The proposed module aims to bring topic modeling to non-specialists using a general-purpose language. |
MaintIE: A Fine-Grained Annotation Schema and Benchmark for Information Extraction from Maintenance Short Texts (2024.lrec-main)
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| Challenge: | Maintenance short texts (MSTs) provide crucial insights into the state and maintenance activities of machines, infrastructure, and other engineered assets. |
| Approach: | They propose a multi-level fine-grained annotation scheme for entity recognition and relation extraction that includes 5 top-level classes and 6 relations tailored to MSTs. |
| Outcome: | The proposed scheme provides high-quality, fine-grained annotations and a coarse-grain corpus of 7,000 texts. |
GottBERT: a pure German Language Model (2024.emnlp-main)
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Raphael Scheible, Johann Frei, Fabian Thomczyk, Henry He, Patric Tippmann, Jochen Knaus, Victor Jaravine, Frank Kramer, Martin Boeker
| Challenge: | Pre-trained language models have advanced natural language processing (NLP) despite the introduction of BERT, single-language models are still relevant. |
| Approach: | They present a German singlelanguage RoBERT model pre-trained exclusively on the German portion of the OSCAR dataset. |
| Outcome: | The GottBERT model outperforms the existing models on Named Entity Recognition and text classification tasks. |