Feature Representation in Convolutional Neural Networks. - Ben Athiwaratkun; Keegan Kang (CoRR, 2015)

Multimodal Word Distributions. - Ben Athiwaratkun; Andrew Gordon Wilson (ACL (1), 2017)

Malware classification with LSTM and GRU language models and a character-level CNN. - Ben Athiwaratkun; Jack W. Stokes (ICASSP, 2017)

Probabilistic FastText for Multi-Sense Word Embeddings. - Ben Athiwaratkun; Andrew Gordon Wilson; Anima Anandkumar (ACL (1), 2018)

Hierarchical Density Order Embeddings. - Ben Athiwaratkun; Andrew Gordon Wilson (ICLR (Poster), 2018)

Improving Consistency-Based Semi-Supervised Learning with Weight Averaging. - Ben Athiwaratkun; Marc Finzi; Pavel Izmailov; Andrew Gordon Wilson (CoRR, 2018)

Adversarial Deep Averaging Networks for Cross-Lingual Sentiment Classification. - Xilun Chen 002; Yu Sun 020; Ben Athiwaratkun; Claire Cardie; Kilian Q. Weinberger (Trans. Assoc. Comput. Linguistics, 2018)

There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average. - Ben Athiwaratkun; Marc Finzi; Pavel Izmailov; Andrew Gordon Wilson (ICLR (Poster), 2019)

Augmented Natural Language for Generative Sequence Labeling. - Ben Athiwaratkun; Cícero Nogueira dos Santos; Jason Krone; Bing Xiang (EMNLP (1), 2020)

Generative Context Pair Selection for Multi-hop Question Answering. - Dheeru Dua; Cícero Nogueira dos Santos; Patrick Ng; Ben Athiwaratkun; Bing Xiang; Matt Gardner 001; Sameer Singh 001 (EMNLP (1), 2021)

Structured Prediction as Translation between Augmented Natural Languages. - Giovanni Paolini; Ben Athiwaratkun; Jason Krone; Jie Ma; Alessandro Achille; Rishita Anubhai; Cícero Nogueira dos Santos; Bing Xiang; Stefano Soatto (ICLR, 2021)

Joint Text and Label Generation for Spoken Language Understanding. - Yang Li; Ben Athiwaratkun; Cícero Nogueira dos Santos; Bing Xiang (CoRR, 2021)

Multi-lingual Evaluation of Code Generation Models. - Ben Athiwaratkun; Sanjay Krishna Gouda; Zijian Wang 002; Xiaopeng Li 002; Yuchen Tian; Ming Tan; Wasi Uddin Ahmad; Shiqi Wang 002; Qing Sun; Mingyue Shang; Sujan Kumar Gonugondla; Hantian Ding; et al. (CoRR, 2022)

Multi-lingual Evaluation of Code Generation Models. - Ben Athiwaratkun; Sanjay Krishna Gouda; Zijian Wang 002; Xiaopeng Li 002; Yuchen Tian; Ming Tan; Wasi Uddin Ahmad; Shiqi Wang 002; Qing Sun; Mingyue Shang; Sujan Kumar Gonugondla; Hantian Ding; et al. (ICLR, 2023)

Towards Greener Yet Powerful Code Generation via Quantization: An Empirical Study. - Xiaokai Wei; Sujan Kumar Gonugondla; Shiqi Wang 002; Wasi Uddin Ahmad; Baishakhi Ray; Haifeng Qian; Xiaopeng Li 002; Varun Kumar; Zijian Wang 002; Yuchen Tian; Qing Sun; Ben Athiwaratkun; et al. (ESEC/SIGSOFT FSE, 2023)

Greener yet Powerful: Taming Large Code Generation Models with Quantization. - Xiaokai Wei; Sujan K. Gonugondla; Wasi Uddin Ahmad; Shiqi Wang 002; Baishakhi Ray; Haifeng Qian; Xiaopeng Li 002; Varun Kumar; Zijian Wang 002; Yuchen Tian; Qing Sun; Ben Athiwaratkun; et al. (CoRR, 2023)

Token Alignment via Character Matching for Subword Completion. - Ben Athiwaratkun; Shiqi Wang 002; Mingyue Shang; Yuchen Tian; Zijian Wang 002; Sujan Kumar Gonugondla; Sanjay Krishna Gouda; Robert Kwiatkowski; Ramesh Nallapati; Parminder Bhatia; Bing Xiang (ACL (Findings), 2024)

Reasoning in Token Economies: Budget-Aware Evaluation of LLM Reasoning Strategies. - Junlin Wang; Siddhartha Jain 001; Dejiao Zhang; Baishakhi Ray; Varun Kumar; Ben Athiwaratkun (EMNLP, 2024)

Bifurcated Attention for Single-Context Large-Batch Sampling. - Ben Athiwaratkun; Sujan Kumar Gonugondla; Sanjay Krishna Gouda; Haifeng Qian; Hantian Ding; Qing Sun; Jun Wang 022; Jiacheng Guo; Liangfu Chen; Parminder Bhatia; Ramesh Nallapati; Sudipta Sengupta; et al. (ICML, 2024)

RedPajama: an Open Dataset for Training Large Language Models. - Maurice Weber; Daniel Y. Fu; Quentin Anthony; Yonatan Oren; Shane Adams; Anton Alexandrov; Xiaozhong Lyu; Huu Nguyen; Xiaozhe Yao; Virginia Adams; Ben Athiwaratkun; Rahul Chalamala; et al. (NeurIPS, 2024)

Token Alignment via Character Matching for Subword Completion. - Ben Athiwaratkun; Shiqi Wang 002; Mingyue Shang; Yuchen Tian; Zijian Wang 002; Sujan Kumar Gonugondla; Sanjay Krishna Gouda; Rob Kwiatkowski; Ramesh Nallapati; Bing Xiang (CoRR, 2024)

Dragonfly: Multi-Resolution Zoom Supercharges Large Visual-Language Model. - Kezhen Chen; Rahul Thapa; Rahul Chalamala; Ben Athiwaratkun; Shuaiwen Leon Song; James Zou 001 (CoRR, 2024)

Scaling Instruction-tuned LLMs to Million-token Contexts via Hierarchical Synthetic Data Generation. - Linda He; Jue Wang; Maurice Weber; Shang Zhu; Ben Athiwaratkun; Ce Zhang (ICLR, 2025)

Training-Free Activation Sparsity in Large Language Models. - James Liu; Pragaash Ponnusamy; Tianle Cai; Han Guo; Yoon Kim; Ben Athiwaratkun (ICLR, 2025)

Mixture-of-Agents Enhances Large Language Model Capabilities. - Junlin Wang; Jue Wang; Ben Athiwaratkun; Ce Zhang; James Zou (ICLR, 2025)

Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping. - Muru Zhang; Mayank Mishra; Zhongzhu Zhou; William Brandon; Jue Wang; Yoon Kim; Jonathan Ragan-Kelley; Shuaiwen Leon Song; Ben Athiwaratkun; Tri Dao (CoRR, 2025)

Scaling Instruction-Tuned LLMs to Million-Token Contexts via Hierarchical Synthetic Data Generation. - Linda He; Jue Wang; Maurice Weber; Shang Zhu; Ben Athiwaratkun; Ce Zhang 001 (CoRR, 2025)

Think Deep, Think Fast: Investigating Efficiency of Verifier-free Inference-time-scaling Methods. - Junlin Wang; Shang Zhu; Jon Saad-Falcon; Ben Athiwaratkun; Qingyang Wu; Jue Wang; Shuaiwen Leon Song; Ce Zhang 001; Bhuwan Dhingra; James Zou 001 (CoRR, 2025)

How Well Can General Vision-Language Models Learn Medicine By Watching Public Educational Videos? - Rahul Thapa; Andrew Li; Qingyang Wu; Bryan He; Yuki Sahashi; Christina Binder; Angela Zhang; Ben Athiwaratkun; Shuaiwen Leon Song; David Ouyang; James Zou 001 (CoRR, 2025)

Improving Model Alignment Through Collective Intelligence of Open-Source LLMS. - Junlin Wang; Roy Xie; Shang Zhu; Jue Wang; Ben Athiwaratkun; Bhuwan Dhingra; Shuaiwen Leon Song; Ce Zhang 001; James Zou 001 (CoRR, 2025)

Disentangling Reasoning and Knowledge in Medical Large Language Models. - Rahul Thapa; Qingyang Wu; Kevin Wu; Harrison Zhang; Angela Zhang; Eric Wu; Haotian Ye; Suhana Bedi; Nevin Aresh; Joseph Boen; Shriya Reddy; Ben Athiwaratkun; et al. (CoRR, 2025)

When Does Divide and Conquer Work for Long Context LLM? A Noise Decomposition Framework. - Zhen Xu 007; Shang Zhu; Jue Wang; Junlin Wang; Ben Athiwaratkun; Chi Wang; James Zou 001; Ce Zhang 001 (CoRR, 2025)

Shrinking the Generation-Verification Gap with Weak Verifiers. - Jon Saad-Falcon; Estefany Kelly Buchanan; Mayee F. Chen; Tzu-Heng Huang; Brendan McLaughlin; Tanvir Bhathal; Shang Zhu; Ben Athiwaratkun; Frederic Sala; Scott W. Linderman; Azalia Mirhoseini; Christopher Ré (CoRR, 2025)

Data Diversification Methods In Alignment Enhance Math Performance In LLMs. - Berkan Dokmeci; Qingyang Wu; Ben Athiwaratkun; Ce Zhang 001; Shuaiwen Leon Song; James Zou 001 (CoRR, 2025)