Most Cited ICML "shape-sensitive factors" Papers
5,975 papers found • Page 26 of 30
Conference
Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
Zheng Huang, Qihui Yang, Dawei Zhou et al.
EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs
Haohui Wang, Yuzhen Mao, Yujun Yan et al.
Active Statistical Inference
Tijana Zrnic, Emmanuel J Candes
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models
YAN WANG, Lihao Wang, Yuning Shen et al.
CHAI: Clustered Head Attention for Efficient LLM Inference
Saurabh Agarwal, Bilge Acun, Basil Hosmer et al.
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis
Patrick Esser, Sumith Kulal, Andreas Blattmann et al.
Deep Demonstration Tracing: Learning Generalizable Imitator Policy for Runtime Imitation from a Single Demonstration
Xiong-Hui Chen, Junyin Ye, Hang Zhao et al.
Policy-conditioned Environment Models are More Generalizable
Ruifeng Chen, Xiong-Hui Chen, Yihao Sun et al.
SILVER: Single-loop variance reduction and application to federated learning
Kazusato Oko, Shunta Akiyama, Denny Wu et al.
Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
Xihaier Luo, Xiaoning Qian, Byung-Jun Yoon
InterLUDE: Interactions between Labeled and Unlabeled Data to Enhance Semi-Supervised Learning
Zhe Huang, Xiaowei Yu, Dajiang Zhu et al.
Using Left and Right Brains Together: Towards Vision and Language Planning
Jun CEN, Chenfei Wu, Xiao Liu et al.
SMaRt: Improving GANs with Score Matching Regularity
Mengfei Xia, Yujun Shen, Ceyuan Yang et al.
ODIN: Disentangled Reward Mitigates Hacking in RLHF
Lichang Chen, Chen Zhu, Jiuhai Chen et al.
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference
Md Musfiqur Rahman, Murat Kocaoglu
Interplay of ROC and Precision-Recall AUCs: Theoretical Limits and Practical Implications in Binary Classification
Martin Mihelich, François Castagnos, Charles Dognin
FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
Yuwei Fu, Haichao Zhang, di wu et al.
On Discrete Prompt Optimization for Diffusion Models
Ruochen Wang, Ting Liu, Cho-Jui Hsieh et al.
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models
Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna et al.
Directly Denoising Diffusion Models
Dan Zhang, Jingjing Wang, Feng Luo
Nearest Neighbour Score Estimators for Diffusion Generative Models
Matthew Niedoba, Dylan Green, Saeid Naderiparizi et al.
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya Singh, Ted Moskovitz, Feilx Hill et al.
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald et al.
Out-of-Domain Generalization in Dynamical Systems Reconstruction
Niclas Göring, Florian Hess, Manuel Brenner et al.
Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
Uri Gadot, Kaixin Wang, Navdeep Kumar et al.
VideoPoet: A Large Language Model for Zero-Shot Video Generation
Dan Kondratyuk, Lijun Yu, Xiuye Gu et al.
Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications
Boyi Wei, Kaixuan Huang, Yangsibo Huang et al.
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Xiwen Chen, Peijie Qiu, Wenhui Zhu et al.
Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks
Subbarao Kambhampati, Karthik Valmeekam, Lin Guan et al.
New Sample Complexity Bounds for Sample Average Approximation in Heavy-Tailed Stochastic Programming
Hongcheng Liu, Jindong Tong
EvTexture: Event-driven Texture Enhancement for Video Super-Resolution
Dachun Kai, Jiayao Lu, Yueyi Zhang et al.
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling
Bairu Hou, Yujian Liu, Kaizhi Qian et al.
Feature Reuse and Scaling: Understanding Transfer Learning with Protein Language Models
Francesca-Zhoufan Li, Ava Amini, Yisong Yue et al.
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
Arvi Jonnarth, Jie Zhao, Michael Felsberg
No Wrong Turns: The Simple Geometry Of Neural Networks Optimization Paths
Charles Guille-Escuret, Hiroki Naganuma, Kilian Fatras et al.
MOMENT: A Family of Open Time-series Foundation Models
Mononito Goswami, Konrad Szafer, Arjun Choudhry et al.
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization
Jialong Guo, Xinghao Chen, Yehui Tang et al.
Counterfactual Image Editing
Yushu Pan, Elias Bareinboim
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Mohammed Muqeeth, Haokun Liu, Yufan Liu et al.
Fast Adversarial Attacks on Language Models In One GPU Minute
Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan et al.
Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty
Kaizhao Liu, Jose Blanchet, Lexing Ying et al.
EvIL: Evolution Strategies for Generalisable Imitation Learning
Silvia Sapora, Gokul Swamy, Christopher Lu et al.
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining
Aaron Li, Robin Netzorg, Zhihan Cheng et al.
Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data
Fahim Tajwar, Anikait Singh, Archit Sharma et al.
On The Statistical Complexity of Offline Decision-Making
Thanh Nguyen-Tang, Raman Arora
Probabilistic Constrained Reinforcement Learning with Formal Interpretability
YANRAN WANG, QIUCHEN QIAN, David Boyle
Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds
Noémie Jaquier, Leonel Rozo, Miguel González-Duque et al.
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong et al.
Light and Optimal Schrödinger Bridge Matching
Nikita Gushchin, Sergei Kholkin, Evgeny Burnaev et al.
Controlled Decoding from Language Models
Sidharth Mudgal, Jong Lee, Harish Ganapathy et al.
On the Duality Between Sharpness-Aware Minimization and Adversarial Training
Yihao Zhang, Hangzhou He, Jingyu Zhu et al.
Liouville Flow Importance Sampler
Yifeng Tian, Nishant Panda, Yen Ting Lin
Offline Training of Language Model Agents with Functions as Learnable Weights
Shaokun Zhang, Jieyu Zhang, Jiale Liu et al.
Scaling Exponents Across Parameterizations and Optimizers
Katie Everett, Lechao Xiao, Mitchell Wortsman et al.
Discovering Symmetry Breaking in Physical Systems with Relaxed Group Convolution
Rui Wang, Elyssa Hofgard, Han Gao et al.
SPADE: Sparsity-Guided Debugging for Deep Neural Networks
Arshia Soltani Moakhar, Eugenia Iofinova, Elias Frantar et al.
Error Feedback Can Accurately Compress Preconditioners
Ionut-Vlad Modoranu, Aleksei Kalinov, Eldar Kurtic et al.
Extreme Compression of Large Language Models via Additive Quantization
Vage Egiazarian, Andrei Panferov, Denis Kuznedelev et al.
AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios
Zhongzhan Huang, Mingfu Liang, Shanshan Zhong et al.
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
Yuji Roh, Qingyun Liu, Huan Gui et al.
Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation
Randall Balestriero, Romain Cosentino, Sarath Shekkizhar
Ameliorate Spurious Correlations in Dataset Condensation
Jiaxing Cui, Ruochen Wang, Yuanhao Xiong et al.
VideoPrism: A Foundational Visual Encoder for Video Understanding
Long Zhao, Nitesh Bharadwaj Gundavarapu, Liangzhe Yuan et al.
Particle Denoising Diffusion Sampler
Angus Phillips, Hai-Dang Dau, Michael Hutchinson et al.
LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits
Chen-Chia Chang, Yikang Shen, Shaoze Fan et al.
Optimistic Multi-Agent Policy Gradient
Wenshuai Zhao, Yi Zhao, Zhiyuan Li et al.
How do Transformers Perform In-Context Autoregressive Learning ?
Michael Sander, Raja Giryes, Taiji Suzuki et al.
Vision Transformers as Probabilistic Expansion from Learngene
Qiufeng Wang, Xu Yang, Haokun Chen et al.
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
Can Yaras, Peng Wang, Laura Balzano et al.
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
Xiangming Gu, Xiaosen Zheng, Tianyu Pang et al.
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné et al.
Modeling Language Tokens as Functionals of Semantic Fields
Zhengqi Pei, Anran Zhang, Shuhui Wang et al.
Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing
Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan
Score-Based Causal Discovery of Latent Variable Causal Models
Ignavier Ng, Xinshuai Dong, Haoyue Dai et al.
DITTO: Diffusion Inference-Time T-Optimization for Music Generation
Zachary Novack, Julian McAuley, Taylor Berg-Kirkpatrick et al.
Language Models as Science Tutors
Alexis Chevalier, Jiayi Geng, Alexander Wettig et al.
Acquisition Conditioned Oracle for Nongreedy Active Feature Acquisition
Michael Valancius, Maxwell Lennon, Junier Oliva
Position: Technical Research and Talent is Needed for Effective AI Governance
Anka Reuel, Lisa Soder, Benjamin Bucknall et al.
Token-Specific Watermarking with Enhanced Detectability and Semantic Coherence for Large Language Models
Mingjia Huo, Sai Ashish Somayajula, Youwei Liang et al.
SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms
Xingrun Xing, Zheng Zhang, Ziyi Ni et al.
Integrated Hardware Architecture and Device Placement Search
Irene Wang, Jakub Tarnawski, Amar Phanishayee et al.
Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization
Kwang-Sung Jun, Jungtaek Kim
Fast Sampling-Based Sketches for Tensors
William Swartworth, David Woodruff
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
Jon Saad-Falcon, Daniel Y Fu, Simran Arora et al.
Diffusion Models Encode the Intrinsic Dimension of Data Manifolds
Jan Stanczuk, Georgios Batzolis, Teo Deveney et al.
Graph Neural Networks Use Graphs When They Shouldn't
Maya Bechler-Speicher, Ido Amos, Ran Gilad-Bachrach et al.
Two Fists, One Heart: Multi-Objective Optimization Based Strategy Fusion for Long-tailed Learning
Zhe Zhao, Pengkun Wang, HaiBin Wen et al.
AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors
Yucen Wang, Shenghua Wan, Le Gan et al.
Data-free Distillation of Diffusion Models with Bootstrapping
Jiatao Gu, Chen Wang, Shuangfei Zhai et al.
What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions
raghav singhal, Mark Goldstein, Rajesh Ranganath
Stochastic Interpolants with Data-Dependent Couplings
Michael Albergo, Mark Goldstein, Nicholas Boffi et al.
Adaptive Sampling of k-Space in Magnetic Resonance for Rapid Pathology Prediction
Chen-Yu Yen, raghav singhal, Umang Sharma et al.
Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
Shuyu Cheng, Yibo Miao, Yinpeng Dong et al.
Self-Rewarding Language Models
Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho et al.
COALA: A Practical and Vision-Centric Federated Learning Platform
Weiming Zhuang, Jian Xu, Chen Chen et al.
Arrows of Time for Large Language Models
Vassilis Papadopoulos, Jérémie Wenger, Clement Hongler
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization
Lukas Gruber, Markus Holzleitner, Johannes Lehner et al.
In-Context Learning Agents Are Asymmetric Belief Updaters
Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.
Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond
Dingzhi Yu, Yunuo Cai, Wei Jiang et al.
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall et al.
FADAS: Towards Federated Adaptive Asynchronous Optimization
Yujia Wang, Shiqiang Wang, Songtao Lu et al.
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits
Jiabin Lin, Shana Moothedath, Namrata Vaswani
A Closer Look at the Limitations of Instruction Tuning
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar et al.
Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
Hyunseok Oh, Youngki Lee
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability
Sepanta Zeighami, Cyrus Shahabi
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
songyang gao, Qiming Ge, Wei Shen et al.
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
Zhiheng Xi, Wenxiang Chen, Boyang Hong et al.
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction
yang zhang, Zhewei Wei, Ye Yuan et al.
Is Kernel Prediction More Powerful than Gating in Convolutional Neural Networks?
Lorenz K. Muller
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization
Sam Reifenstein, Timothee Leleu, Yoshihisa Yamamoto
Incorporating probabilistic domain knowledge into deep multiple instance learning
Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri et al.
Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
Shokichi Takakura, Taiji Suzuki
In-Context Language Learning: Architectures and Algorithms
Ekin Akyürek, Bailin Wang, Yoon Kim et al.
Gated Linear Attention Transformers with Hardware-Efficient Training
Songlin Yang, Bailin Wang, Yikang Shen et al.
Agnostic Sample Compression Schemes for Regression
Idan Attias, Steve Hanneke, Aryeh Kontorovich et al.
ArtWhisperer: A Dataset for Characterizing Human-AI Interactions in Artistic Creations
Kailas Vodrahalli, James Zou
Dealing With Unbounded Gradients in Stochastic Saddle-point Optimization
Gergely Neu, Nneka Okolo
Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation
Weiming Liu, Xiaolin Zheng, Chaochao Chen et al.
Masked Face Recognition with Generative-to-Discriminative Representations
Shiming Ge, Weijia Guo, Chenyu Li et al.
Recovering the Pre-Fine-Tuning Weights of Generative Models
Eliahu Horwitz, Jonathan Kahana, Yedid Hoshen
Plug-in Performative Optimization
Licong Lin, Tijana Zrnic
Understanding Finetuning for Factual Knowledge Extraction
Gaurav Ghosal, Tatsunori Hashimoto, Aditi Raghunathan
Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge
Yufei Huang, Odin Zhang, Lirong Wu et al.
Estimating Canopy Height at Scale
Jan Pauls, Max Zimmer, Una Kelly et al.
Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning
Lirong Wu, Yijun Tian, Haitao Lin et al.
Position: Cracking the Code of Cascading Disparity Towards Marginalized Communities
Golnoosh Farnadi, Mohammad Havaei, Negar Rostamzadeh
A Global Geometric Analysis of Maximal Coding Rate Reduction
Peng Wang, Huikang Liu, Druv Pai et al.
The Pitfalls of Next-Token Prediction
Gregor Bachmann, Vaishnavh Nagarajan
Failures Are Fated, But Can Be Faded: Characterizing and Mitigating Unwanted Behaviors in Large-Scale Vision and Language Models
Som Sagar, Aditya Taparia, Ransalu Senanayake
Navigating Scaling Laws: Compute Optimality in Adaptive Model Training
Sotiris Anagnostidis, Gregor Bachmann, Imanol Schlag et al.
A Language Model’s Guide Through Latent Space
Dimitri von Rütte, Sotiris Anagnostidis, Gregor Bachmann et al.
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
Bingheng Li, Linxin Yang, Yupeng Chen et al.
One Meta-tuned Transformer is What You Need for Few-shot Learning
Xu Yang, Huaxiu Yao, Ying WEI
Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought
Zhen-Yu Zhang, Siwei Han, Huaxiu Yao et al.
Conformal Prediction for Deep Classifier via Label Ranking
Jianguo Huang, HuaJun Xi, Linjun Zhang et al.
Position: TrustLLM: Trustworthiness in Large Language Models
Yue Huang, Lichao Sun, Haoran Wang et al.
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu et al.
Multiplicative Weights Update, Area Convexity and Random Coordinate Descent for Densest Subgraph Problems
Ta Duy Nguyen, Alina Ene
Representation Surgery: Theory and Practice of Affine Steering
Shashwat Singh, Shauli Ravfogel, Jonathan Herzig et al.
SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models
Dongyang Liu, Renrui Zhang, Longtian Qiu et al.
Accelerating Federated Learning with Quick Distributed Mean Estimation
Ran Ben Basat, Shay Vargaftik, Amit Portnoy et al.
From Classification Accuracy to Proper Scoring Rules: Elicitability of Probabilistic Top List Predictions
Johannes Resin
Layerwise Proximal Replay: A Proximal Point Method for Online Continual Learning
Jinsoo Yoo, Yunpeng Liu, Frank Wood et al.
A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
Agustinus Kristiadi, Felix Strieth-Kalthoff, Marta Skreta et al.
Rate-Optimal Policy Optimization for Linear Markov Decision Processes
Uri Sherman, Alon Cohen, Tomer Koren et al.
Fast Peer Adaptation with Context-aware Exploration
Long Ma, Yuanfei Wang, Fangwei Zhong et al.
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova et al.
Learning to Infer Generative Template Programs for Visual Concepts
R. Kenny Jones, Siddhartha Chaudhuri, Daniel Ritchie
Gibbs Sampling of Continuous Potentials on a Quantum Computer
Arsalan Motamedi, Pooya Ronagh
Dual Operating Modes of In-Context Learning
Ziqian Lin, Kangwook Lee
D-Flow: Differentiating through Flows for Controlled Generation
Heli Ben-Hamu, Omri Puny, Itai Gat et al.
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
Xiang Cheng, Yuxin Chen, Suvrit Sra
Unveiling the Dynamics of Information Interplay in Supervised Learning
Kun Song, Zhiquan Tan, Bochao Zou et al.
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Yair Schiff, Chia Hsiang Kao, Aaron Gokaslan et al.
Integrating Global Context Contrast and Local Sensitivity for Blind Image Quality Assessment
Xudong Li, Runze Hu, Jingyuan Zheng et al.
Adaptive Feature Selection for No-Reference Image Quality Assessment by Mitigating Semantic Noise Sensitivity
Xudong Li, Timin Gao, Runze Hu et al.
Can AI Assistants Know What They Don't Know?
Qinyuan Cheng, Tianxiang Sun, Xiangyang Liu et al.
Low-Rank Bandits via Tight Two-to-Infinity Singular Subspace Recovery
Yassir Jedra, William Réveillard, Stefan Stojanovic et al.
Classification Under Strategic Self-Selection
Guy Horowitz, Yonatan Sommer, Moran Koren et al.
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration
Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim et al.
Estimating Distributional Treatment Effects in Randomized Experiments: Machine Learning for Variance Reduction
Undral Byambadalai, Tatsushi Oka, Shota Yasui
USTAD: Unified Single-model Training Achieving Diverse Scores for Information Retrieval
Seungyeon Kim, Ankit Singh Rawat, Manzil Zaheer et al.
StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization
Songhua Liu, Xin Jin, Xingyi Yang et al.
Multi-layer Rehearsal Feature Augmentation for Class-Incremental Learning
Bowen Zheng, Da-Wei Zhou, Han-Jia Ye et al.
On the Role of Edge Dependency in Graph Generative Models
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos et al.
Consistent Long-Term Forecasting of Ergodic Dynamical Systems
Vladimir Kostic, Karim Lounici, Prune Inzerilli et al.
Visual-Text Cross Alignment: Refining the Similarity Score in Vision-Language Models
Jinhao Li, Haopeng Li, Sarah Erfani et al.
Learning to Explore in POMDPs with Informational Rewards
Annie Xie, Logan M. Bhamidipaty, Evan Liu et al.
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu et al.
Can Mamba Learn How To Learn? A Comparative Study on In-Context Learning Tasks
Jong Ho Park, Jaden Park, Zheyang Xiong et al.
Structure Your Data: Towards Semantic Graph Counterfactuals
Angeliki Dimitriou, Maria Lymperaiou, Giorgos Filandrianos et al.
Efficient Adaptation in Mixed-Motive Environments via Hierarchical Opponent Modeling and Planning
Yizhe Huang, Anji Liu, Fanqi Kong et al.
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Nikhil Sardana, Jacob Portes, Alexandre (Sasha) Doubov et al.
Accelerating Look-ahead in Bayesian Optimization: Multilevel Monte Carlo is All you Need
Shangda Yang, Vitaly Zankin, Maximilian Balandat et al.
A Persuasive Approach to Combating Misinformation
Safwan Hossain, Andjela Mladenovic, Yiling Chen et al.
Fine-tuning Reinforcement Learning Models is Secretly a Forgetting Mitigation Problem
Maciej Wołczyk, Bartłomiej Cupiał, Mateusz Ostaszewski et al.
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language Models
Akhil Kedia, Mohd Abbas Zaidi, Sushil Khyalia et al.
HALC: Object Hallucination Reduction via Adaptive Focal-Contrast Decoding
Zhaorun Chen, Zhuokai Zhao, HONGYIN LUO et al.
Jetfire: Efficient and Accurate Transformer Pretraining with INT8 Data Flow and Per-Block Quantization
Haocheng Xi, Yuxiang Chen, Kang Zhao et al.
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
Hyunki Seong, Hyunchul Shim
High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
Yuxuan Yin, Yu Wang, Peng Li
A Unified Adaptive Testing System Enabled by Hierarchical Structure Search
Junhao Yu, Yan Zhuang, Zhenya Huang et al.
Observable Propagation: Uncovering Feature Vectors in Transformers
Jacob Dunefsky, Arman Cohan
Complexity Matters: Feature Learning in the Presence of Spurious Correlations
GuanWen Qiu, Da Kuang, Surbhi Goel
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
Yuhui Li, Fangyun Wei, Chao Zhang et al.
Copyright Traps for Large Language Models
Matthieu Meeus, Igor Shilov, Manuel Faysse et al.
PAGER: Accurate Failure Characterization in Deep Regression Models
Jayaraman J. Thiagarajan, Vivek Narayanaswamy, Puja Trivedi et al.
Policy Evaluation for Variance in Average Reward Reinforcement Learning
Shubhada Agrawal, Prashanth L.A., Siva Maguluri
Interpreting Equivariant Representations
Andreas Abildtrup Hansen, Anna Calissano, Aasa Feragen
Risk Estimation in a Markov Cost Process: Lower and Upper Bounds
Gugan Chandrashekhar Mallika Thoppe, Prashanth L.A., Sanjay Bhat
Physics and Lie symmetry informed Gaussian processes
David Dalton, Dirk Husmeier, Hao Gao
Characterizing Truthfulness in Large Language Model Generations with Local Intrinsic Dimension
Fan Yin, Jayanth Srinivasa, Kai-Wei Chang
Robust Yet Efficient Conformal Prediction Sets
Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
On the Trajectory Regularity of ODE-based Diffusion Sampling
Defang Chen, Zhenyu Zhou, Can Wang et al.
CF-OPT: Counterfactual Explanations for Structured Prediction
Germain Vivier-Ardisson, Alexandre Forel, Axel Parmentier et al.
Differentiable Weightless Neural Networks
Alan Bacellar, Zachary Susskind, Mauricio Breternitz Jr et al.
Adaptive Observation Cost Control for Variational Quantum Eigensolvers
Christopher J. Anders, Kim A. Nicoli, Bingting Wu et al.
Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds
Yuyang Zhang, Shahriar Talebi, Na Li
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević et al.
Kepler codebook
Junrong Lian, Ziyue Dong, Pengxu Wei et al.