DP
Dimitris Papailiopoulos
cs.LGstat.MLcs.DCcs.ITmath.ITcs.AIcs.CLmath.OCcs.DScs.NI
On Valency
published · living versionsW_u7fa5rax·v1 · currentpublished
MLSys: The New Frontier of Machine Learning Systems
with Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen +64
1 version
Preprints & journals
80 papers in the corpus · 2010–2026Scaling Discovery through Test-Time Communication2609.21032v1 · Jongho Park, Vasilis Kontonis, Shivam Garg et al.2026 · 0 citationsarXiv
You Don't Need to Run Every Eval2606.24020v2 · Yuchen Zeng, Dimitris Papailiopoulos2026 · 0 citationsarXiv
Wait, Wait, Wait... Why Do Reasoning Models Loop?2512.12895v2 · Charilaos Pipis, Shivam Garg, Vasilis Kontonis et al.2025 · 0 citationsarXiv
SuperThoughts: Reasoning Tokens in Superposition2606.13862v1 · Zheyang Xiong, Shivam Garg, Max Yu et al.2026 · 0 citationsarXiv
Provable Deterministic Leverage Score Sampling1404.1530v3 · Dimitris Papailiopoulos, Anastasios Kyrillidis, Christos Boutsidis2014 · 68 citationsarXiv
Sparse Principal Component of a Rank-deficient Matrix1106.1651v1 · Megasthenis Asteris, Dimitris S. Papailiopoulos, George N. Karystinos2011 · 14 citationsarXiv
ECHO: Terminal Agents Learn World Models for Free2605.24517v1 · Vaishnavi Shrivastava, Piero Kauffmann, Ahmed Awadallah et al.2026 · 0 citationsarXiv
Open-World Evaluations for Measuring Frontier AI Capabilities2605.20520v1 · Sayash Kapoor, Peter Kirgis, Andrew Schwartz et al.2026 · 0 citationsarXiv
MEMENTO: Teaching LLMs to Manage Their Own Context2604.09852v1 · Vasilis Kontonis, Yuchen Zeng, Shivam Garg et al.2026 · 0 citationsarXiv
Endless Terminals: Scaling RL Environments for Terminal Agents2601.16443v3 · Kanishk Gandhi, Shivam Garg, Noah D. Goodman et al.2026 · 0 citationsarXiv
ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning2512.00831v2 · Yuchen Zeng, Shuibai Zhang, Wonjun Kang et al.2025 · 0 citationsarXiv
Not All Bits Are Equal: Scale-Dependent Memory Optimization Strategies for Reasoning Models2510.10964v1 · Junhyuck Kim, Ethan Ewer, Taehong Moon et al.2025 · 0 citationsarXiv
Extrapolation by Association: Length Generalization Transfer in Transformers2506.09251v2 · Ziyang Cai, Nayoung Lee, Avi Schwarzschild et al.2025 · 0 citationsarXiv
VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data2502.06737v2 · Thomas Zeng, Shuibai Zhang, Shutong Wu et al.2025 · 0 citationsarXiv
Phi-4-reasoning Technical Report2504.21318v1 · Marah Abdin, Sahaj Agarwal, Ahmed Awadallah et al.2025 · 1 citationarXiv
Self-Improving Transformers Overcome Easy-to-Hard and Length Generalization Challenges2502.01612v2 · Nayoung Lee, Ziyang Cai, Avi Schwarzschild et al.2025 · 1 citationarXiv
Task Vectors in In-Context Learning: Emergence, Formation, and Benefit2501.09240v1 · Liu Yang, Ziqian Lin, Kangwook Lee et al.2025 · 0 citationsarXiv
Lexico: Extreme KV Cache Compression via Sparse Coding over Universal Dictionaries2412.08890v1 · Junhyuck Kim, Jongho Park, Jaewoong Cho et al.2024 · 1 citationarXiv
From Artificial Needles to Real Haystacks: Improving Retrieval Capabilities in LLMs by Finetuning on Synthetic Data2406.19292v2 · Zheyang Xiong, Vasilis Papageorgiou, Kangwook Lee et al.2024 · 1 citationarXiv
Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition2410.05603v1 · Zheyang Xiong, Ziyang Cai, John Cooper et al.2024 · 0 citationsarXiv
Predictive Pipelined Decoding: A Compute-Latency Trade-off for Exact LLM Decoding2307.05908v2 · Seongjun Yang, Gibbeum Lee, Jaewoong Cho et al.2023 · 1 citationarXiv
CHAI: Clustered Head Attention for Efficient LLM Inference2403.08058v2 · Saurabh Agarwal, Bilge Acun, Basil Hosmer et al.2024 · 2 citationsarXiv
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks2402.04248v2 · Jongho Park, Jaeseung Park, Zheyang Xiong et al.2024 · 10 citationsarXiv
Looped Transformers are Better at Learning Learning Algorithms2311.12424v3 · Liu Yang, Kangwook Lee, Robert Nowak et al.2023 · 0 citationsarXiv
How Well Can Transformers Emulate In-context Newton's Method?2403.03183v1 · Angeliki Giannou, Liu Yang, Tianhao Wang et al.2024 · 0 citationsarXiv
Dissecting Chain-of-Thought: Compositionality through In-Context Filtering and Learning2305.18869v2 · Yingcong Li, Kartik Sreenivasan, Angeliki Giannou et al.2023 · 2 citationsarXiv
Prompted LLMs as Chatbot Modules for Long Open-domain Conversation2305.04533v1 · Gibbeum Lee, Volker Hartmann, Jongho Park et al.2023 · 33 citationsarXiv
Mini-Batch Optimization of Contrastive Loss2307.05906v1 · Jaewoong Cho, Kartik Sreenivasan, Keon Lee et al.2023 · 2 citationsarXiv
Teaching Arithmetic to Small Transformers2307.03381v1 · Nayoung Lee, Kartik Sreenivasan, Jason D. Lee et al.2023 · 7 citationsarXiv
PathProx: A Proximal Gradient Algorithm for Weight Decay Regularized Deep Neural Networks2210.03069v4 · Liu Yang, Jifan Zhang, Joseph Shenouda et al.2022 · 0 citationsarXiv
The Expressive Power of Tuning Only the Normalization Layers2302.07937v2 · Angeliki Giannou, Shashank Rajput, Dimitris Papailiopoulos2023 · 0 citationsarXiv
Cuttlefish: Low-Rank Model Training without All the Tuning2305.02538v2 · Hongyi Wang, Saurabh Agarwal, Pongsakorn U-chupala et al.2023 · 0 citationsarXiv
Transformers as Algorithms: Generalization and Stability in In-context Learning2301.07067v2 · Yingcong Li, M. Emrullah Ildiz, Dimitris Papailiopoulos et al.2023 · 11 citationsarXiv
Looped Transformers as Programmable Computers2301.13196v1 · Angeliki Giannou, Shashank Rajput, Jy-yong Sohn et al.2023 · 3 citationsarXiv
Utilizing Language-Image Pretraining for Efficient and Robust Bilingual Word Alignment2205.11616v2 · Tuan Dinh, Jy-yong Sohn, Shashank Rajput et al.2022 · 0 citationsarXiv
LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks2206.06565v4 · Tuan Dinh, Yuchen Zeng, Ruisu Zhang et al.2022 · 55 citationsarXiv
Rare Gems: Finding Lottery Tickets at Initialization2202.12002v2 · Kartik Sreenivasan, Jy-yong Sohn, Liu Yang et al.2022 · 12 citationsarXiv
GenLabel: Mixup Relabeling using Generative Models2201.02354v1 · Jy-yong Sohn, Liang Shang, Hongxu Chen et al.2022 · 2 citationsarXiv
Permutation-Based SGD: Is Random Optimal?2102.09718v2 · Shashank Rajput, Kangwook Lee, Dimitris Papailiopoulos2021 · 1 citationarXiv
Finding Everything within Random Binary Networks2110.08996v2 · Kartik Sreenivasan, Shashank Rajput, Jy-yong Sohn et al.2021 · 1 citationarXiv
On the Utility of Gradient Compression in Distributed Training Systems2103.00543v3 · Saurabh Agarwal, Hongyi Wang, Shivaram Venkataraman et al.2021 · 18 citationsarXiv
An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks2106.07724v1 · Shashank Rajput, Kartik Sreenivasan, Dimitris Papailiopoulos et al.2021 · 9 citationsarXiv
Optimal Lottery Tickets via SubsetSum: Logarithmic Over-Parameterization is Sufficient2006.07990v2 · Ankit Pensia, Shashank Rajput, Alliot Nagle et al.2020 · 35 citationsarXiv
Pufferfish: Communication-efficient Models At No Extra Cost2103.03936v1 · Hongyi Wang, Saurabh Agarwal, Dimitris Papailiopoulos2021 · 5 citationsarXiv
Bad Global Minima Exist and SGD Can Reach Them1906.02613v2 · Shengchao Liu, Dimitris Papailiopoulos, Dimitris Achlioptas2019 · 37 citationsarXiv
Accordion: Adaptive Gradient Communication via Critical Learning Regime Identification2010.16248v1 · Saurabh Agarwal, Hongyi Wang, Kangwook Lee et al.2020 · 13 citationsarXiv
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning2007.05084v1 · Hongyi Wang, Kartik Sreenivasan, Shashank Rajput et al.2020 · 109 citationsarXiv
Closing the convergence gap of SGD without replacement2002.10400v6 · Shashank Rajput, Anant Gupta, Dimitris Papailiopoulos2020 · 9 citationsarXiv
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation1907.12205v2 · Shashank Rajput, Hongyi Wang, Zachary Charles et al.2019 · 47 citationsarXiv
Federated Learning with Matched Averaging2002.06440v1 · Hongyi Wang, Mikhail Yurochkin, Yuekai Sun et al.2020 · 97 citationsarXiv
Career total: 125 works. 80 are in this corpus.Showing the 50 most recent.
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