Most Cited ICLR "rule-based reinforcement learning" Papers

Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy

Ishank Juneja, Carlee Joe-Wong, Osman Yagan

gRNAde: Geometric Deep Learning for 3D RNA inverse design

Chaitanya Joshi, Arian Jamasb, Ramon Viñas et al.

From an LLM Swarm to a PDDL-empowered Hive: Planning Self-executed Instructions in a Multi-modal Jungle

Kaustubh Vyas, Damien Graux, Yijun Yang et al.

Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding

Akash Kumar, Zsolt Kira, Yogesh S Rawat

JPEG Inspired Deep Learning

Ahmed Hussien Salamah, Kaixiang Zheng, Yiwen Liu et al.

Remove Symmetries to Control Model Expressivity and Improve Optimization

Liu Ziyin, Yizhou Xu, Isaac Chuang

TC-MoE: Augmenting Mixture of Experts with Ternary Expert Choice

Shen Yan, Xingyan Bin, Sijun Zhang et al.

Repurposing in AI: A Distinct Approach or an Extension of Creative Problem Solving?

Aissatou Diallo, Antonis Bikakis, Luke Dickens et al.

InstantPortrait: One-Step Portrait Editing via Diffusion Multi-Objective Distillation

Zhixin Lai, Keqiang Sun, Fu-Yun Wang et al.

Adam Exploits $\ell_\infty$-geometry of Loss Landscape via Coordinate-wise Adaptivity

Shuo Xie, Mohamad Amin Mohamadi, Zhiyuan Li

Decoupled Subgraph Federated Learning

Javad Aliakbari, Johan Östman, Alexandre Graell i Amat

Diffusion Bridge Implicit Models

Kaiwen Zheng, Guande He, Jianfei Chen et al.

SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem

Margalit Glasgow

Beyond Worst-Case Dimensionality Reduction for Sparse Vectors

Sandeep Silwal, David Woodruff, Qiuyi (Richard) Zhang

Elucidating the Preconditioning in Consistency Distillation

Kaiwen Zheng, Guande He, Jianfei Chen et al.

Homomorphism Counts as Structural Encodings for Graph Learning

Linus Bao, Emily Jin, Michael Bronstein et al.

Chain-of-Thought Provably Enables Learning the (Otherwise) Unlearnable

Chenxiao Yang, Zhiyuan Li, David Wipf

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization

Zhe Li, Bicheng Ying, Zidong Liu et al.

Improving Data Efficiency via Curating LLM-Driven Rating Systems

Jinlong Pang, Jiaheng Wei, Ankit Parag Shah et al.

Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape View

Kaiyue Wen, Zhiyuan Li, Jason Wang et al.

nGPT: Normalized Transformer with Representation Learning on the Hypersphere

Ilya Loshchilov, Cheng-Ping Hsieh, Simeng Sun et al.

A Coefficient Makes SVRG Effective

Yida Yin, Zhiqiu Xu, Zhiyuan Li et al.

PhysPDE: Rethinking PDE Discovery and a Physical HYpothesis Selection Benchmark

Mingquan Feng, Yixin Huang, Yizhou Liu et al.

Near-Optimal Policy Identification in Robust Constrained Markov Decision Processes via Epigraph Form

Toshinori Kitamura, Tadashi Kozuno, Wataru Kumagai et al.

Everything, Everywhere, All at Once: Is Mechanistic Interpretability Identifiable?

Maxime Méloux, Silviu Maniu, François Portet et al.

Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression

Juno Kim, Dimitri Meunier, Arthur Gretton et al.

ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference

Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets et al.

CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs

Dung Nguyen, Thang Phan, Nam Le Hai et al.

Compute-Optimal LLMs Provably Generalize Better with Scale

Marc Finzi, Sanyam Kapoor, Diego Granziol et al.

On the Benefits of Attribute-Driven Graph Domain Adaptation

Ruiyi Fang, Bingheng Li, zhao kang et al.

UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP

Wenzheng Pan, Hao Xiong, Jiale Ma et al.

Robust LLM safeguarding via refusal feature adversarial training

Lei Yu, Virginie Do, Karen Hambardzumyan et al.

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Hojoon Lee, Dongyoon Hwang, Donghu Kim et al.

TabDiff: a Mixed-type Diffusion Model for Tabular Data Generation

Juntong Shi, Minkai Xu, Harper Hua et al.

ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities

Peng Xu, Wei Ping, Xianchao Wu et al.

Boltzmann priors for Implicit Transfer Operators

Juan Viguera Diez, Mathias Schreiner, Ola Engkvist et al.

Tracking the Copyright of Large Vision-Language Models through Parameter Learning Adversarial Images

Yubo Wang, Jianting Tang, Liu et al.

Adversarial Mixup Unlearning

Zhuoyi Peng, Yixuan Tang, Yi Yang

Biologically Constrained Barrel Cortex Model Integrates Whisker Inputs and Replicates Key Brain Network Dynamics

Tianfang Zhu, Dongli Hu, Jiandong Zhou et al.

Optimality of Matrix Mechanism on $\ell_p^p$-metric

Zongrui Zou, Jingcheng Liu, Jalaj Upadhyay

Login

Towards Understanding the Universality of Transformers for Next-Token Prediction

Michael Sander, Gabriel Peyré

ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering

Ilya Shenbin, Sergey Nikolenko

Adapting to Distribution Shift by Visual Domain Prompt Generation

Zhixiang Chi, Li Gu, Tao Zhong et al.

Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning

Menglong Zhang, Fuyuan Qian, Quanying Liu

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text

Nate Gruver, Anuroop Sriram, Andrea Madotto et al.

Online Clustering with Nearly Optimal Consistency

T-H. Hubert Chan, Shaofeng Jiang, Tianyi Wu et al.

The Geometry of Categorical and Hierarchical Concepts in Large Language Models

Kiho Park, Yo Joong Choe, Yibo Jiang et al.

On the Stability of Iterative Retraining of Generative Models on their own Data

Quentin Bertrand, Joey Bose, Alexandre Duplessis et al.

One-shot Empirical Privacy Estimation for Federated Learning

Galen Andrew, Peter Kairouz, Sewoong Oh et al.

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari et al.

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma et al.

Watch Less, Do More: Implicit Skill Discovery for Video-Conditioned Policy

Wang, Zongqing Lu

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches

Jiayuan Gu, Sean Kirmani, Paul Wohlhart et al.

Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns

Hongbin Huang, Minghua Chen, Xiao Qiao

From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities

Wanpeng Zhang, Zilong Xie, Yicheng Feng et al.

RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment

Kevin Yang, Dan Klein, Asli Celikyilmaz et al.

Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs

Yuxin Zhang, Lirui Zhao, Mingbao Lin et al.

Learning to Act from Actionless Videos through Dense Correspondences

Po-Chen Ko, Jiayuan Mao, Yilun Du et al.

ZipIt! Merging Models from Different Tasks without Training

George Stoica, Daniel Bolya, Jakob Bjorner et al.

Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression

Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk et al.

In-context Autoencoder for Context Compression in a Large Language Model

Tao Ge, Hu Jing, Lei Wang et al.

Lost in Prediction: Why Social Media Narratives Don't Help Macroeconomic Forecasting?

Almog Gueta, Roi Reichart, Amir Feder et al.

DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning

Jing Xiong, Zixuan Li, Chuanyang Zheng et al.

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection

Xiangyu Dong, Xingyi Zhang, Sibo WANG

GIM: Learning Generalizable Image Matcher From Internet Videos

Xuelun Shen, zhipeng cai, Wei Yin et al.

DiffEnc: Variational Diffusion with a Learned Encoder

Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi et al.

GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher

Youliang Yuan, Wenxiang Jiao, Wenxuan Wang et al.

LEGO-Prover: Neural Theorem Proving with Growing Libraries

Haiming Wang, Huajian Xin, Chuanyang Zheng et al.

Procedural Synthesis of Synthesizable Molecules

Michael Sun, Alston Lo, Minghao Guo et al.

Conditional Testing based on Localized Conformal $p$-values

Xiaoyang Wu, Lin Lu, Zhaojun Wang et al.

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization

Yang Jin, Kun Xu, Kun Xu et al.

Function Vectors in Large Language Models

Eric Todd, Millicent Li, Arnab Sen Sharma et al.

3DitScene: Editing Any Scene via Language-guided Disentangled Gaussian Splatting

Qihang Zhang, Yinghao Xu, Chaoyang Wang et al.

The False Promise of Imitating Proprietary Language Models

Arnav Gudibande, Eric Wallace, Charlie Snell et al.

Retrieval-Enhanced Contrastive Vision-Text Models

Ahmet Iscen, Mathilde Caron, Alireza Fathi et al.

Navigating Neural Space: Revisiting Concept Activation Vectors to Overcome Directional Divergence

Frederik Pahde, Maximilian Dreyer, Moritz Weckbecker et al.

The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction

Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra

Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng et al.

Time-to-Event Pretraining for 3D Medical Imaging

Zepeng Frazier Huo, Jason Fries, Alejandro Lozano et al.

Denoising Autoregressive Transformers for Scalable Text-to-Image Generation

Jiatao Gu, Yuyang Wang, Yizhe Zhang et al.

Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement

Bryan Bo Cao, Lawrence OGorman, Michael Coss et al.

Bad-PFL: Exploiting Backdoor Attacks against Personalized Federated Learning

Mingyuan Fan, Zhanyi Hu, Fuyi Wang et al.

On the Role of General Function Approximation in Offline Reinforcement Learning

Chenjie Mao, Qiaosheng Zhang, Zhen Wang et al.

Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Yilan Zhang, Yingxue XU, Jianqi Chen et al.

Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework

Ryan Lucas, Rahul Mazumder

Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks

Hung Quang Nguyen, Hieu Nguyen, Anh Ta et al.

CR-CTC: Consistency regularization on CTC for improved speech recognition

Zengwei Yao, Wei Kang, Xiaoyu Yang et al.

Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning

Chengxing Jia, Chen-Xiao Gao, Hao Yin et al.

An Illustrated Guide to Automatic Sparse Differentiation

Adrian Hill, Guillaume Dalle, Alexis Montoison

Language Model Self-improvement by Reinforcement Learning Contemplation

Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li et al.

Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost

Yuan Gao, WEIZHONG ZHANG, Wenhan Luo et al.

Robust System Identification: Finite-sample Guarantees and Connection to Regularization

Hank Park, Grani A. Hanasusanto, Yingying Li

Imitation Learning from Observation with Automatic Discount Scheduling

Yuyang Liu, Weijun Dong, Yingdong Hu et al.

Offline RL with Observation Histories: Analyzing and Improving Sample Complexity

Joey Hong, Anca Dragan, Sergey Levine

Predictive, scalable and interpretable knowledge tracing on structured domains

Hanqi Zhou, Robert Bamler, Charley Wu et al.

Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation

Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon et al.

A Statistical Framework for Ranking LLM-based Chatbots

Siavash Ameli, Siyuan Zhuang, Ion Stoica et al.

The LLM Surgeon

Tycho van der Ouderaa, Markus Nagel, Mart van Baalen et al.

Can Transformers Capture Spatial Relations between Objects?

Chuan Wen, Dinesh Jayaraman, Yang Gao

InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior

Chenguo Lin, Yadong MU

NExUME: Adaptive Training and Inference for DNNs under Intermittent Power Environments

Cyan Subhra Mishra, Deeksha Chaudhary, Jack Sampson et al.

PEARL: Parallel Speculative Decoding with Adaptive Draft Length

Tianyu Liu, Yun Li, Qitan Lv et al.

A General Framework for User-Guided Bayesian Optimization

Carl Hvarfner, Frank Hutter, Luigi Nardi

SmartPlay : A Benchmark for LLMs as Intelligent Agents

Yue Wu, Xuan Tang, Tom Mitchell et al.

RingAttention with Blockwise Transformers for Near-Infinite Context

Hao Liu, Matei Zaharia, Pieter Abbeel

Capturing the Temporal Dependence of Training Data Influence

Jiachen (Tianhao) Wang, Dawn Song, James Y Zou et al.

Active Test-Time Adaptation: Theoretical Analyses and An Algorithm

Shurui Gui, Xiner Li, Shuiwang Ji

Unveiling Options with Neural Network Decomposition

Mahdi Alikhasi, Levi Lelis

Reconciling Model Multiplicity for Downstream Decision Making

Ally Du, Dung Daniel Ngo, Steven Wu

Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning

Shengyuan Hu, Yiwei Fu, Steven Wu et al.

FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Tri Dao

Are Models Biased on Text without Gender-related Language?

Catarina Belém, Preethi Seshadri, Yasaman Razeghi et al.

On Stationary Point Convergence of PPO-Clip

Ruinan Jin, Shuai Li, Baoxiang Wang

Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness

Eli Chien, Pan Li

The Human-AI Substitution game: active learning from a strategic labeler

Tom Yan, Chicheng Zhang

ARB-LLM: Alternating Refined Binarizations for Large Language Models

Zhiteng Li, Xianglong Yan, Tianao Zhang et al.

Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks

David Robin, Kevin Scaman, marc lelarge

OSTQuant: Refining Large Language Model Quantization with Orthogonal and Scaling Transformations for Better Distribution Fitting

Xing Hu, Yuan Cheng, Dawei Yang et al.

GOttack: Universal Adversarial Attacks on Graph Neural Networks via Graph Orbits Learning

Zulfikar Alom, Tran Gia Bao Ngo, Murat Kantarcioglu et al.

Masks, Signs, And Learning Rate Rewinding

Advait Gadhikar, Rebekka Burkholz

Regret-Optimal List Replicable Bandit Learning: Matching Upper and Lower Bounds

Michael Chen, A. Pavan, N. V. Vinodchandran et al.

Efficient Imitation under Misspecification

Nicolas Espinosa Dice, Sanjiban Choudhury, Wen Sun et al.

RAIN: Your Language Models Can Align Themselves without Finetuning

Yuhui Li, Fangyun Wei, Jinjing Zhao et al.

Learning From Simplicial Data Based on Random Walks and 1D Convolutions

Florian Frantzen, Michael Schaub

Multimodal Molecular Pretraining via Modality Blending

Qiying Yu, Yudi Zhang, yuyan ni et al.

Sample-Efficient Multi-Agent RL: An Optimization Perspective

Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.

From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module

Claudio Battiloro, Indro Spinelli, Lev Telyatinkov et al.

Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features

Annie Chen, Yoonho Lee, Amrith Setlur et al.

Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality

Xuxi Chen, Yu Yang, Zhangyang Wang et al.

Probe Pruning: Accelerating LLMs through Dynamic Pruning via Model-Probing

Qi Le, Enmao Diao, Ziyan Wang et al.

Discrete Distribution Networks

Lei Yang

MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning

Zohar Rimon, Tom Jurgenson, Orr Krupnik et al.

Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes

Thiziri Nait Saada, Alireza Naderi, Jared Tanner

Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model

Rundong He, Yicong Dong, Lan-Zhe Guo et al.

RETSim: Resilient and Efficient Text Similarity

Marina Zhang, Owen Vallis, Aysegul Bumin et al.

ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization

Chen Bo Calvin Zhang, Zhang-Wei Hong, Aldo Pacchiano et al.

Grid Cell-Inspired Fragmentation and Recall for Efficient Map Building

Jaedong Hwang, Zhang-Wei Hong, Eric Chen et al.

Neural Spectral Methods: Self-supervised learning in the spectral domain

Yiheng Du, Nithin Chalapathi, Aditi Krishnapriyan

Learning the greatest common divisor: explaining transformer predictions

François Charton

DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenes

Hengwei Bian, Lingdong Kong, Haozhe Xie et al.

Separating common from salient patterns with Contrastive Representation Learning

Robin Louiset, Edouard Duchesnay, Grigis Antoine et al.

Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection

Zhiyuan Cheng, Hongjun Choi, Shiwei Feng et al.

MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba

Masakazu Yoshimura, Teruaki Hayashi, Yota Maeda

Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects

Chunming He, Kai Li, Yachao Zhang et al.

CBQ: Cross-Block Quantization for Large Language Models

Xin Ding, Xiaoyu Liu, Zhijun Tu et al.

Identifying Representations for Intervention Extrapolation

Sorawit (James) Saengkyongam, Elan Rosenfeld, Pradeep K Ravikumar et al.

SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases

Yang Liu, Jiashun Cheng, Haihong Zhao et al.

DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$

Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom et al.

Learning-Augmented Frequent Directions

Anders Aamand, Justin Chen, Siddharth Gollapudi et al.

MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions

Yekun Chai, Haoran Sun, Huang Fang et al.

Structuring Benchmark into Knowledge Graphs to Assist Large Language Models in Retrieving and Designing Models

Hanmo Liu, Shimin Di, Jialiang Wang et al.

Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning

Harsh Chaudhari, Giorgio Severi, Alina Oprea et al.

Locality-Aware Graph Rewiring in GNNs

Federico Barbero, Ameya Velingker, Amin Saberi et al.

Adaptive Instrument Design for Indirect Experiments

Yash Chandak, Shiv Shankar, Vasilis Syrgkanis et al.

Learning 3D Particle-based Simulators from RGB-D Videos

William Whitney, Tatiana Lopez-Guevara, Tobias Pfaff et al.

Space and time continuous physics simulation from partial observations

Steeven Janny, Madiha Nadri, Julie Digne et al.

Adaptive Retention & Correction: Test-Time Training for Continual Learning

Haoran Chen, Micah Goldblum, Zuxuan Wu et al.

Optimal Sample Complexity for Average Reward Markov Decision Processes

Shengbo Wang, Jose Blanchet, Peter Glynn

IntersectionZoo: Eco-driving for Benchmarking Multi-Agent Contextual Reinforcement Learning

Vindula Jayawardana, Baptiste Freydt, Ao Qu et al.

Interpreting CLIP's Image Representation via Text-Based Decomposition

Yossi Gandelsman, Alexei Efros, Jacob Steinhardt

Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods

Zijian Liu, Zhengyuan Zhou

Time-Efficient Reinforcement Learning with Stochastic Stateful Policies

Firas Al-Hafez, Guoping Zhao, Jan Peters et al.

NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization

Gen Li, Lu Yin, Jie Ji et al.

Time After Time: Deep-Q Effect Estimation for Interventions on When and What to do

Yoav Wald, Mark Goldstein, Yonathan Efroni et al.

GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks

Peter Müller, Lukas Faber, Karolis Martinkus et al.

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model

Karsten Roth, Lukas Thede, A. Sophia Koepke et al.

LR0.FM: LOW-RESOLUTION ZERO-SHOT CLASSIFICATION BENCHMARK FOR FOUNDATION MODELS

Priyank Pathak, Shyam Marjit, Shruti Vyas et al.

On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks

Shengjie Zhou, Lue Tao, Yuzhou Cao et al.

Efficient Score Matching with Deep Equilibrium Layers

Yuhao Huang, Qingsong Wang, Akwum Onwunta et al.

Rethinking Label Poisoning for GNNs: Pitfalls and Attacks

Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski

A path-norm toolkit for modern networks: consequences, promises and challenges

Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.

LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement

Zhifan Ye, Kejing Xia, Yonggan Fu et al.

Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization

Ian Gemp, Luke Marris, Georgios Piliouras

Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation

Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao et al.

Radar: Fast Long-Context Decoding for Any Transformer

Yongchang Hao, Mengyao Zhai, Hossein Hajimirsadeghi et al.

FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing

Yuren Cong, Mengmeng Xu, Christian Simon et al.

LabelDP-Pro: Learning with Label Differential Privacy via Projections

Badih Ghazi, Yangsibo Huang, Pritish Kamath et al.

Learning the Optimal Stopping for Early Classification within Finite Horizons via Sequential Probability Ratio Test

Akinori F. Ebihara, Taiki Miyagawa, Kazuyuki Sakurai et al.

Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models

Jung Hwan Heo, Jeonghoon Kim, Beomseok Kwon et al.

Robust Similarity Learning with Difference Alignment Regularization

Shuo Chen, Gang Niu, Chen Gong et al.

Diving Segmentation Model into Pixels

Chen Gan, Zihao Yin, Kelei He et al.

A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks

Haruo Hosoya

Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models

Gabriele Corso, Yilun Xu, Valentin De Bortoli et al.

Visually Guided Decoding: Gradient-Free Hard Prompt Inversion with Language Models

Donghoon Kim, Minji Bae, Kyuhong Shim et al.

Tight Time Complexities in Parallel Stochastic Optimization with Arbitrary Computation Dynamics

Alexander Tyurin

AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents

Jake Grigsby, Jim Fan, Yuke Zhu

Improving Offline RL by Blending Heuristics

Sinong Geng, Aldo Pacchiano, Andrey Kolobov et al.

Delta-AI: Local objectives for amortized inference in sparse graphical models

Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin et al.

V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection

Yichao Shen, Zigang Geng, YUHUI YUAN et al.

Lagrangian Flow Networks for Conservation Laws

Fabricio Arend Torres, Marcello Negri, Marco Inversi et al.

WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions

Can Xu, Qingfeng Sun, Kai Zheng et al.

Looking Backward: Streaming Video-to-Video Translation with Feature Banks

Feng Liang, Akio Kodaira, Chenfeng Xu et al.

Why Does the Effective Context Length of LLMs Fall Short?

Chenxin An, Jun Zhang, Ming Zhong et al.

Modelling complex vector drawings with stroke-clouds

Alexander Ashcroft, Ayan Das, Yulia Gryaditskaya et al.

Multi-View Causal Representation Learning with Partial Observability

Dingling Yao, Danru Xu, Sébastien Lachapelle et al.

PILOT: An $\mathcal{O}(1/K)$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation

Zhuqing Liu, Xin Zhang, Jia Liu et al.

Universal Humanoid Motion Representations for Physics-Based Control

Zhengyi Luo, Jinkun Cao, Josh Merel et al.

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning

Caleb Chuck, Fan Feng, Carl Qi et al.

$\text{I}^2\text{AM}$: Interpreting Image-to-Image Latent Diffusion Models via Bi-Attribution Maps

Junseo Park, Hyeryung Jang