Automated Screening of Antibacterial Nanoparticle Literature: Dataset Curation and Model Evaluation (2026.eacl-long)
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Alperen Ozturk, Şaziye Betül Özateş, Sophia Bahar Root, Angela Violi, Nicholas Kotov, J. Scott VanEpps, Emine Sumeyra Turali Emre
| Challenge: | Antimicrobial resistance is a growing global health threat, driving interest in nanoparticle-based alternatives to conventional antibiotics. |
| Approach: | They propose to use machine learning to classify scientific abstracts using inorganic nanoparticles with intrinsic antibacterial properties. |
| Outcome: | The proposed method distinguishes intrinsic antibacterial NPs from studies focusing on drug carriers or surface-bound applications. |
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Mohammad Golam Sohrab, Khoa N.A. Duong, Ikeda Masami, Goran Topić, Yayoi Natsume-Kitatani, Masakata Kuroda, Mari Nogami Itoh, Hiroya Takamura
| Challenge: | BiomedCurator uses state-of-the-art natural language processing techniques to extract structured data from scientific articles. |
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Autonomous Data Selection with Zero-shot Generative Classifiers for Mathematical Texts (2025.findings-acl)
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| Challenge: | Existing methods that require human annotations or training a dedicated data filter to curate high-quality mathematical texts are based on autonomous data selection. |
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Automating Document Discovery in the Systematic Review Process: How to Use Chaff to Extract Wheat (L18-1)
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| Challenge: | Systematic reviews address research questions by comprehensively examining the entire published literature. |
| Approach: | They compare the impact of different schemes for choosing positive and negative examples from the different screening stages on the training of automated systems. |
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Accelerating Antibiotic Discovery with Large Language Models and Knowledge Graphs (2025.acl-industry)
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| Challenge: | Antimicrobial resistance (AMR) is one of the top ten global public health threats . pharmaceutical industries face high costs (over $1 billion), long timelines, and a high failure rate . |
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LiGen: Active Lipid Generation via a Molecular Language Model (2026.acl-long)
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| Challenge: | Lipid nanoparticles (LNPs) can deliver cargos to tumor and immune cells . traditional approaches rely on experimental screening and expert judgment . |
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| Outcome: | The proposed method outperforms baseline methods on multiple cell lines and achieves a 30% improvement over the current methods. |
Detecting Contradictory COVID-19 Drug Efficacy Claims from Biomedical Literature (2023.acl-short)
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| Challenge: | During times of pandemic, treatment options are limited, and developing new drug treatments is infeasible in the short-term. |
| Approach: | They propose to use a natural language inference problem to automatically identify contradictory claims about COVID-19 drug efficacy. |
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INSIGHTBUDDY-AI: Medication Extraction and Entity Linking using Pre-Trained Language Models and Ensemble Learning (2025.naacl-srw)
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| Challenge: | InsightBuddy-AI is a system for extracting medication mentions and their associated attributes. |
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A Dataset for N-ary Relation Extraction of Drug Combinations (2022.naacl-main)
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Aryeh Tiktinsky, Vijay Viswanathan, Danna Niezni, Dana Meron Azagury, Yosi Shamay, Hillel Taub-Tabib, Tom Hope, Yoav Goldberg
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Label Agnostic Pre-training for Zero-shot Text Classification (2023.findings-acl)
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| Challenge: | Existing approaches to text classification assume a fixed set of labels . however, in real-world applications, there exists an infinite label space for describing a given text . |
| Approach: | They propose two new methods that inject aspect-level understanding into pre-trained models at train time to improve zero-shot generalization. |
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PubMedQA: A Dataset for Biomedical Research Question Answering (D19-1)
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| Challenge: | PubMedQA is a biomedical question answering dataset based on PubMed abstracts . 68.1% accuracy is achieved, compared to single human performance of 78.0% . |
| Approach: | They propose a biomedical question answering dataset from PubMed abstracts . the dataset is annotated by experts and has 1k instances of QA . |
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