MUST-CNN: A Multilayer Shift-and-Stitch Deep Convolutional Architecture for Sequence-Based Protein Structure Prediction. - Zeming Lin; Jack Lanchantin; Yanjun Qi (AAAI, 2016)

DeepChrome: deep-learning for predicting gene expression from histone modifications. - Ritambhara Singh; Jack Lanchantin; Gabriel Robins; Yanjun Qi (Bioinform., 2016)

Deep Motif: Visualizing Genomic Sequence Classifications. - Jack Lanchantin; Ritambhara Singh; Zeming Lin; Yanjun Qi (CoRR, 2016)

Deep GDashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. - Jack Lanchantin; Ritambhara Singh; Beilun Wang; Yanjun Qi (CoRR, 2016)

Memory Matching Networks for Genomic Sequence Classification. - Jack Lanchantin; Ritambhara Singh; Yanjun Qi (ICLR (Workshop), 2017)

Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin. - Ritambhara Singh; Jack Lanchantin; Arshdeep Sekhon; Yanjun Qi (NIPS, 2017)

GaKCo: A Fast Gapped k-mer String Kernel Using Counting. - Ritambhara Singh; Arshdeep Sekhon; Kamran Kowsari; Jack Lanchantin; Beilun Wang; Yanjun Qi (ECML/PKDD (1), 2017)

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. - Jack Lanchantin; Ritambhara Singh; Beilun Wang; Yanjun Qi (PSB, 2017)

Prototype Matching Networks for Large-Scale Multi-label Genomic Sequence Classification. - Jack Lanchantin; Arshdeep Sekhon; Ritambhara Singh; Yanjun Qi (CoRR, 2017)

Black-Box Generation of Adversarial Text Sequences to Evade Deep Learning Classifiers. - Ji Gao; Jack Lanchantin; Mary Lou Soffa; Yanjun Qi (IEEE Symposium on Security and Privacy Workshops, 2018)

Exploring the Naturalness of Buggy Code with Recurrent Neural Networks. - Jack Lanchantin; Ji Gao (CoRR, 2018)

Neural Message Passing for Multi-label Classification. - Jack Lanchantin; Arshdeep Sekhon; Yanjun Qi (ECML/PKDD (2), 2019)

Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction. - Ritambhara Singh; Jack Lanchantin; Gabriel Robins; Yanjun Qi (IEEE ACM Trans. Comput. Biol. Bioinform., 2019)

Reevaluating Adversarial Examples in Natural Language. - John X. Morris; Eli Lifland; Jack Lanchantin; Yangfeng Ji; Yanjun Qi (EMNLP (Findings), 2020)

FastSK: fast sequence analysis with gapped string kernels. - Derrick Blakely; Eamon Collins; Ritambhara Singh; Andrew P. Norton; Jack Lanchantin; Yanjun Qi (Bioinform., 2020)

Graph convolutional networks for epigenetic state prediction using both sequence and 3D genome data. - Jack Lanchantin; Yanjun Qi (Bioinform., 2020)

Transfer learning for predicting virus-host protein interactions for novel virus sequences. - Jack Lanchantin; Tom Weingarten; Arshdeep Sekhon; Clint Miller; Yanjun Qi (BCB, 2021)

General Multi-Label Image Classification With Transformers. - Jack Lanchantin; Tianlu Wang; Vicente Ordonez; Yanjun Qi (CVPR, 2021)

A Data Source for Reasoning Embodied Agents. - Jack Lanchantin; Sainbayar Sukhbaatar; Gabriel Synnaeve; Yuxuan Sun 004; Kavya Srinet; Arthur Szlam (AAAI, 2023)

Robustness of Named-Entity Replacements for In-Context Learning. - Saeed Goodarzi; Nikhil Kagita; Dennis Minn; Shufan Wang; Roberto Dessì; Shubham Toshniwal; Adina Williams; Jack Lanchantin; Koustuv Sinha (EMNLP (Findings), 2023)

Learning to Reason and Memorize with Self-Notes. - Jack Lanchantin; Shubham Toshniwal; Jason Weston; Arthur Szlam; Sainbayar Sukhbaatar (NeurIPS, 2023)

Compositional Interfaces for Compositional Generalization. - Jelena Luketina; Jack Lanchantin; Sainbayar Sukhbaatar; Arthur Szlam (CoLLAs, 2024)

TOOLVERIFIER: Generalization to New Tools via Self-Verification. - Dheeraj Mekala; Jason Weston; Jack Lanchantin; Roberta Raileanu; Maria Lomeli; Jingbo Shang; Jane Dwivedi-Yu (EMNLP (Findings), 2024)

Adaptive Decoding via Latent Preference Optimization. - Shehzaad Dhuliawala; Ilia Kulikov; Ping Yu; Asli Celikyilmaz; Jason Weston; Sainbayar Sukhbaatar; Jack Lanchantin (CoRR, 2024)

Diverse Preference Optimization. - Jack Lanchantin; Angelica Chen; Shehzaad Dhuliawala; Ping Yu; Jason Weston; Sainbayar Sukhbaatar; Ilia Kulikov (CoRR, 2025)

LLM Pretraining with Continuous Concepts. - Jihoon Tack; Jack Lanchantin; Jane Yu; Andrew Cohen; Ilia Kulikov; Janice Lan; Shibo Hao; Yuandong Tian; Jason Weston; Xian Li 003 (CoRR, 2025)

Bridging Offline and Online Reinforcement Learning for LLMs. - Jack Lanchantin; Angelica Chen; Janice Lan; Xian Li 003; Swarnadeep Saha; Tianlu Wang; Jing Xu; Ping Yu; Weizhe Yuan; Jason E. Weston; Sainbayar Sukhbaatar; Ilia Kulikov (CoRR, 2025)

NaturalThoughts: Selecting and Distilling Reasoning Traces for General Reasoning Tasks. - Yang Li; Youssef Emad; Karthik Padthe; Jack Lanchantin; Weizhe Yuan; Thao Nguyen; Jason Weston; Shang-Wen Li 001; Dong Wang; Ilia Kulikov; Xian Li 003 (CoRR, 2025)

CoT-Self-Instruct: Building high-quality synthetic prompts for reasoning and non-reasoning tasks. - Ping Yu; Jack Lanchantin; Tianlu Wang; Weizhe Yuan; Olga Golovneva; Ilia Kulikov; Sainbayar Sukhbaatar; Jason Weston; Jing Xu (CoRR, 2025)

OptimalThinkingBench: Evaluating Over and Underthinking in LLMs. - Pranjal Aggarwal; Seungone Kim; Jack Lanchantin; Sean Welleck; Jason Weston; Ilia Kulikov; Swarnadeep Saha (CoRR, 2025)

Jointly Reinforcing Diversity and Quality in Language Model Generations. - Tianjian Li; Yiming Zhang; Ping Yu; Swarnadeep Saha; Daniel Khashabi; Jason Weston; Jack Lanchantin; Tianlu Wang (CoRR, 2025)

LLM Output Homogenization is Task Dependent. - Shomik Jain; Jack Lanchantin; Maximilian Nickel; Karen Ullrich; Ashia Wilson; Jamelle Watson-Daniels (CoRR, 2025)