Papers with open-source library
DeepPavlov Strikes Back: A Toolkit for Improving LLM Reliability and Trustworthiness (2026.eacl-demo)
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| Challenge: | a new version of an open-source library for natural language processing (NLP) is released . the library is easy to use, flexible, and works with many languages. |
| Approach: | They introduce a new version of an open-source library for natural language processing (NLP) it supports both traditional NLP tasks and new tasks needed to enhance LLMs truthfulness and reliability. |
| Outcome: | The new version of DeepPavlov supports both traditional and new tasks . it is easy to use, flexible, and works with many languages . |
Finite-state script normalization and processing utilities: The Nisaba Brahmic library (2021.eacl-demos)
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| Challenge: | a library for low-level processing of brahmic scripts is available for free. |
| Approach: | They propose an open-source library for efficient low-level processing of ten major South Asian Brahmic scripts. |
| Outcome: | The proposed library supports low-level processing of ten major south Asian Brahmic scripts. |
Transformers: State-of-the-Art Natural Language Processing (2020.emnlp-demos)
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Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, Alexander Rush
| Challenge: | Transformers is an open-source library that aims to open up advances in natural language processing to the wider machine learning community. |
| Approach: | they propose an open-source library that aims to open up advances in machine learning to the wider community. |
| Outcome: | Transformers is an open-source library with the goal of opening up these advances to the wider machine learning community. |
Edu-ConvoKit: An Open-Source Library for Education Conversation Data (2024.naacl-demo)
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| Challenge: | Edu-ConvoKit is an open-source library for analyzing education conversation data. |
| Approach: | They introduce Edu-ConvoKit, an open-source library for conversation data analysis. |
| Outcome: | The open-source library handles pre-processing, annotation and analysis of education conversation data. |
GLiNER2: Schema-Driven Multi-Task Learning for Structured Information Extraction (2025.emnlp-demos)
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| Challenge: | Existing solutions for information extraction (IE) require specialized models for different tasks or require expensive large language models. |
| Approach: | They propose a framework that enhances the original GLiNER architecture to support named entity recognition, text classification, and hierarchical structured data extraction within a single efficient model. |
| Outcome: | The proposed framework improves performance across diverse IE tasks and accessibility compared to LLM-based alternatives. |
Adapters: A Unified Library for Parameter-Efficient and Modular Transfer Learning (2023.emnlp-demo)
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Clifton Poth, Hannah Sterz, Indraneil Paul, Sukannya Purkayastha, Leon Engländer, Timo Imhof, Ivan Vulić, Sebastian Ruder, Iryna Gurevych, Jonas Pfeiffer
| Challenge: | Adapters is an open-source library that unifies parameter-efficient and modular transfer learning in large language models. |
| Approach: | They propose to integrate 10 different methods into a unified interface for parameter-efficient and modular transfer learning in large language models. |
| Outcome: | The proposed library is able to perform on multiple NLP tasks and is open-source. |
OpenDelta: A Plug-and-play Library for Parameter-efficient Adaptation of Pre-trained Models (2023.acl-demo)
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| Challenge: | Existing implementations that modify the code of the backbone PTMs and hard-code specific delta tuning methods for each PTM have limited the practicality and flexibility of delta tuning. |
| Approach: | They propose an open-source library that provides a plug-and-play implementation of delta tuning methods for pre-trained models. |
| Outcome: | The proposed methods eliminate the need to modify the backbone PTMs’ code, making OpenDelta compatible with different, even novel PTM. |
string2string: A Modern Python Library for String-to-String Algorithms (2024.acl-demos)
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| Challenge: | Notable algorithms include the Smith-Waterman algorithm for pairwise local alignment, the Hirschberg algorithm for global alignment, and the Wagner-Fischer algorithm for edit distance. |
| Approach: | **string2string** is an open-source library that offers efficient algorithms for string-to-string problems. |
| Outcome: | **string2string** is an open-source library that offers efficient algorithms for string-to-string problems. |
NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation (2023.emnlp-demo)
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| Challenge: | Existing open source repositories expose a multitude of programming languages, libraries, and implementation differences, hindering reproducibility and extensibility. |
| Approach: | NewsRecLib is an open-source library for training and evaluating neural news recommendation models. |
| Outcome: | The open-source library provides implementations of several prominent neural models, training methods, standard evaluation benchmarks, and evaluation metrics for news recommendation. |
Ecco: An Open Source Library for the Explainability of Transformer Language Models (2021.acl-demo)
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| Challenge: | Existing models that use the Transformer architecture are lag behind our ability to scale them. |
| Approach: | They propose an open-source library for the explainability of Transformer-based NLP models that captures, analyzes, visualizes, and interactively explores the inner mechanics of these models. |
| Outcome: | The proposed tools capture, analyze, visualize, and explore the inner workings of Transformer-based language models. |
Xinference: Making Large Model Serving Easy (2024.emnlp-demo)
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| Challenge: | Open-source large models are rapidly catching up with the closed-source models . however, many current inference tools are not as simple and convenient to use. |
| Approach: | They develop an open-source library to simplify the deployment and management of large models. |
| Outcome: | The proposed library outperforms open-source models and offers high throughput and low latency. |
Arcee’s MergeKit: A Toolkit for Merging Large Language Models (2024.emnlp-industry)
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Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, Luke Meyers, Vladimir Karpukhin, Brian Benedict, Mark McQuade, Jacob Solawetz
| Challenge: | Open-source language models can merge their parameters to improve performance and versatility without additional training. |
| Approach: | They propose to integrate model checkpoints into powerful multitask models without additional training. |
| Outcome: | the library has facilitated the merging of thousands of models, contributing to some of the world’s most powerful open-source model checkpoints. |
AutoTrain: No-code training for state-of-the-art models (2024.emnlp-demo)
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| Challenge: | AutoTrain is an open-source, no code tool/library which can be used to train models on custom datasets. |
| Approach: | They propose an open-source, no-code tool/library to train models on custom datasets. |
| Outcome: | The open-source, no-code tool/library can be used to train models on custom datasets. |
TokenSmith: Streamlining Data Editing, Search, and Inspection for Large-Scale Language Model Training and Interpretability (2025.emnlp-demos)
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Mohammad Aflah Khan, Ameya Godbole, Johnny Wei, Ryan Yixiang Wang, James Flemings, Krishna P. Gummadi, Willie Neiswanger, Robin Jia
| Challenge: | Existing workflows for pretraining large language models are cumbersome, fragmented and inaccessible. |
| Approach: | They propose an open-source library for editing, inspection, and analysis of large language model datasets. |
| Outcome: | TokenSmith is an open-source library for editing, inspection, and analysis of large language model datasets. |
AutoChecklist: Composable Pipelines for Checklist Generation and Scoring with LLM-as-a-Judge (2026.acl-demo)
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| Challenge: | AutoChecklist is an open-source library that unifies checklist-based evaluation into composable pipelines. |
| Approach: | They propose an open-source library that unifies checklist-based evaluation into composable pipelines. |
| Outcome: | The open-source library unifies checklist-based evaluation into composable pipelines. |
Mergenetic: a Simple Evolutionary Model Merging Library (2025.acl-demo)
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| Challenge: | Recent work shows that combining model merging with evolutionary algorithms can boost performance, but there is currently no library for experimenting with different evolutionary algorithms and merging methods. |
| Approach: | They propose an open-source library for evolutionary model merging that enables easy composition of merging methods and evolutionary algorithms while incorporating lightweight fitness estimators to reduce evaluation costs. |
| Outcome: | The proposed library produces competitive results across languages and tasks using modest hardware. |
Coreference Resolution in FreeLing 4.0 (L18-1)
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| Challenge: | FreeLing is an open-source library for NLP with more than fifteen years of existence and a widespread user community. |
| Approach: | They propose to port RelaxCor to FreeLing to solve the integration problems . they propose to use two strategies and a rough evaluation of the integration results . |
| Outcome: | The proposed integration of RelaxCor into FreeLing solves the problems found in a shared task scenario. |
Simple Yet Powerful: An Overlooked Architecture for Nested Named Entity Recognition (2022.coling-1)
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| Challenge: | Named Entity Recognition (NER) is an important task in Natural Language Processing that aims to identify text spans belonging to predefined categories. |
| Approach: | They propose to revisit the Multiple LSTM-CRF (MLC) model, a simple, overlooked, yet powerful approach based on training independent sequence labeling models for each entity type. |
| Outcome: | The proposed model achieves state-of-the-art results in the Chilean Waiting List corpus by including pre-trained language models. |
FonBund: A Library for Combining Cross-lingual Phonological Segment Data (L18-1)
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| Challenge: | Speech and language technology is currently only available for a tiny fraction of the world's languages. |
| Approach: | They propose to map phonetic segments in International Phonetic Alphabet into multiple articulatory feature representations using a free-source library. |
| Outcome: | The proposed library can be easily modified to support new phonological segment inventories. |