Most Cited ICLR "selective knowledge removal" Papers
6,124 papers found • Page 24 of 31
Conference
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence
Dharmesh Tailor, Alvaro Correia, Eric Nalisnick et al.
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
Chenxi Sun, Hongyan Li, Yaliang Li et al.
Reveal Object in Lensless Photography via Region Gaze and Amplification
Xiangjun Yin, Huihui Yue
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning
Yichuan Li, Xiyao Ma, Sixing Lu et al.
Fast Imitation via Behavior Foundation Models
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati et al.
Vertical Federated Learning with Missing Features During Training and Inference
Pedro Valdeira, Shiqiang Wang, Yuejie Chi
Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information
Xinhao Zhong, Bin Chen, Hao Fang et al.
Robust Gymnasium: A Unified Modular Benchmark for Robust Reinforcement Learning
Shangding Gu, Laixi Shi, Muning Wen et al.
TUVF: Learning Generalizable Texture UV Radiance Fields
An-Chieh Cheng, Xueting Li, Sifei Liu et al.
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis et al.
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden et al.
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Yehui Tang, Hao Xiong, Nianzu Yang et al.
Open-Set Graph Anomaly Detection via Normal Structure Regularisation
Qizhou Wang, Guansong Pang, Mahsa Salehi et al.
Symmetric Single Index Learning
Aaron Zweig, Joan Bruna
Functional Interpolation for Relative Positions improves Long Context Transformers
Shanda Li, Chong You, Guru Guruganesh et al.
Convergence of Bayesian Bilevel Optimization
Shi Fu, Fengxiang He, Xinmei Tian et al.
Balancing Bias in Two-sided Markets for Fair Stable Matchings
Siyuan Wu, Leong Hou U, Panagiotis Karras
Reward-Free Curricula for Training Robust World Models
Marc Rigter, Minqi Jiang, Ingmar Posner
KBLaM: Knowledge Base augmented Language Model
Xi Wang, Taketomo Isazawa, Liana Mikaelyan et al.
PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding
Wei Chow, Jiageng Mao, Boyi Li et al.
On Trajectory Augmentations for Off-Policy Evaluation
Ge Gao, Qitong Gao, Xi Yang et al.
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness
Fran Jelenić, Josip Jukić, Martin Tutek et al.
From Complexity to Clarity: Analytical Expressions of Deep Neural Network Weights via Clifford Algebra and Convexity
Mert Pilanci
PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
Ségolène Martin, Anne Gagneux, Paul Hagemann et al.
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
Mingde Zhao, Safa Alver, Harm Seijen et al.
P2Seg: Pointly-supervised Segmentation via Mutual Distillation
Zipeng Wang, Xuehui Yu, Xumeng Han et al.
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination
Manley Roberts, Himanshu Thakur, Christine Herlihy et al.
Building Blocks of Differentially Private Training
Mahmoud Hegazy, Aymeric Dieuleveut
ADOPD: A Large-Scale Document Page Decomposition Dataset
Jiuxiang Gu, Xiangxi Shi, Jason Kuen et al.
Federated Few-Shot Class-Incremental Learning
Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Soleimani Abyaneh, Mahrokh Boroujeni, Hsiu-Chin Lin et al.
Vision and Language Synergy for Rehearsal Free Continual Learning
Muhammad Anwar Masum, Mahardhika Pratama, Savitha Ramasamy et al.
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong, Zhiqiang Tang, Tong He et al.
SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding
Jian Chen, Ruiyi Zhang, Yufan Zhou et al.
Fourier Head: Helping Large Language Models Learn Complex Probability Distributions
Nate Gillman, Daksh Aggarwal, Michael Freeman et al.
Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
Fabian Akkerman, Julius Luy, Wouter van Heeswijk et al.
Minimalistic Predictions for Online Class Constraint Scheduling
Dorian Guyot, Alexandra Lassota
Transformer Fusion with Optimal Transport
Moritz Imfeld, Jacopo Graldi, Marco Giordano et al.
Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning
Berken Utku Demirel, Christian Holz
Teaching Large Language Models to Self-Debug
Xinyun Chen, Maxwell Lin, Nathanael Schaerli et al.
REFACTOR: Learning to Extract Theorems from Proofs
Jin Zhou, Yuhuai Wu, Qiyang Li et al.
OWL: A Large Language Model for IT Operations
Hongcheng Guo, Jian Yang, Jiaheng Liu et al.
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Yang Yang, Wenhai Wang, Zhe Chen et al.
Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks
Hanling Tian, Yuhang Liu, Mingzhen He et al.
A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model
Zecheng Hao, Xinyu Shi, Zihan Huang et al.
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
Jiawei Sun, Kailai Li, Ruoxin Chen et al.
Find A Winning Sign: Sign Is All We Need to Win the Lottery
Junghun Oh, Sungyong Baik, Kyoung Mu Lee
SWE-Search: Enhancing Software Agents with Monte Carlo Tree Search and Iterative Refinement
Antonis Antoniades, Albert Örwall, Kexun Zhang et al.
Handling Delay in Real-Time Reinforcement Learning
Ivan Anokhin, Rishav Rishav, Matt Riemer et al.
Compositional Conservatism: A Transductive Approach in Offline Reinforcement Learning
Yeda Song, Dongwook Lee, Gunhee Kim
Multimodal Learning Without Labeled Multimodal Data: Guarantees and Applications
Paul Liang, Chun Kai Ling, Yun Cheng et al.
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
Kuofeng Gao, Yang Bai, Jindong Gu et al.
Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
Andrew Jesson, Nicolas Beltran-Velez, David Blei
PhyloGFN: Phylogenetic inference with generative flow networks
MING YANG ZHOU, Zichao Yan, Elliot Layne et al.
Enhancing Group Fairness in Online Settings Using Oblique Decision Forests
Somnath Basu Roy Chowdhury, Nicholas Monath, Ahmad Beirami et al.
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen et al.
Video Action Differencing
James Burgess, Xiaohan Wang, Yuhui Zhang et al.
Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates
Xiuchuan Li, Jun Wang, Tongliang Liu
GenEx: Generating an Explorable World
TaiMing Lu, Tianmin Shu, Alan Yuille et al.
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav, Nicholas Monath, Manzil Zaheer et al.
Training LLMs over Neurally Compressed Text
Brian Lester, Jaehoon Lee, Jeffrey Pennington et al.
Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement
Kotaro Yoshida, Yuji Naraki, Takafumi Horie et al.
Instance-dependent Early Stopping
Suqin Yuan, Runqi Lin, Lei Feng et al.
SFS: Smarter Code Space Search improves LLM Inference Scaling
Jonathan Light, Yue Wu, Yiyou Sun et al.
Weatherproofing Retrieval for Localization with Generative AI and Geometric Consistency
Yannis Kalantidis, Mert Bulent SARIYILDIZ, Rafael Rezende et al.
A Differentially Private Clustering Algorithm for Well-Clustered Graphs
Weiqiang He, Hendrik Fichtenberger, Pan Peng
TypedThinker: Diversify Large Language Model Reasoning with Typed Thinking
Danqing Wang, Jianxin Ma, Fei Fang et al.
OCCAM: Towards Cost-Efficient and Accuracy-Aware Classification Inference
Dujian Ding, Bicheng Xu, Laks Lakshmanan
StringLLM: Understanding the String Processing Capability of Large Language Models
Xilong Wang, Hao Fu, Jindong Wang et al.
Personalized Visual Instruction Tuning
Renjie Pi, Jianshu Zhang, Tianyang Han et al.
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Chenhui Deng, Zichao Yue, Zhiru Zhang
SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution
Wenlong Zhang, Xiaohui Li, Xiangyu Chen et al.
Rethinking Backdoor Attacks on Dataset Distillation: A Kernel Method Perspective
Ming-Yu Chung, Sheng-Yen Chou, Chia-Mu Yu et al.
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models
Sheng Shen, Le Hou, Yanqi Zhou et al.
Synergistic Patch Pruning for Vision Transformer: Unifying Intra- & Inter-Layer Patch Importance
Yuyao Zhang, Lan Wei, Nikolaos Freris
Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport
Lvmin Zhang, Anyi Rao, Maneesh Agrawala
Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
yisheng xiao, Juntao Li, Zechen Sun et al.
USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields
Moyang Li, Peng Wang, Lingzhe Zhao et al.
Identifying latent state transitions in non-linear dynamical systems
Çağlar Hızlı, Çağatay Yıldız, Matthias Bethge et al.
Selective Task Group Updates for Multi-Task Optimization
Wooseong Jeong, Kuk-Jin Yoon
From Few to Many: Self-Improving Many-Shot Reasoners Through Iterative Optimization and Generation
Xingchen Wan, Han Zhou, Ruoxi Sun et al.
PhiNets: Brain-inspired Non-contrastive Learning Based on Temporal Prediction Hypothesis
Satoki Ishikawa, Makoto Yamada, Han Bao et al.
Self-Supervised Diffusion Models for Electron-Aware Molecular Representation Learning
Gyoung S. Na, Chanyoung Park
Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency
Bowen Song, Soo Min Kwon, Zecheng Zhang et al.
A Unified Framework for Bayesian Optimization under Contextual Uncertainty
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano et al.
Explore Theory of Mind: program-guided adversarial data generation for theory of mind reasoning
Melanie Sclar, Jane Dwivedi-Yu, Maryam Fazel-Zarandi et al.
P$^2$OT: Progressive Partial Optimal Transport for Deep Imbalanced Clustering
Chuyu Zhang, Hui Ren, Xuming He
Linear Recurrences Accessible to Everyone
Felix Sarnthein
DreamCraft3D: Hierarchical 3D Generation with Bootstrapped Diffusion Prior
Jingxiang Sun, Bo Zhang, Ruizhi Shao et al.
Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
Julius Aka, Johannes Brunnemann, Jörg Eiden et al.
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh, Greg Heinrich, Hongxu Yin et al.
Nemesis: Normalizing the Soft-prompt Vectors of Vision-Language Models
Shuai Fu, Shuai Fu, Xiequn Wang et al.
More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing
Sagi Shaier, Francisco Pereira, Katharina Kann et al.
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
Tianqi Chen, Shujian Zhang, Mingyuan Zhou
Has the Deep Neural Network learned the Stochastic Process? An Evaluation Viewpoint
Harshit Kumar, Beomseok Kang, Biswadeep Chakraborty et al.
Beyond Mere Token Analysis: A Hypergraph Metric Space Framework for Defending Against Socially Engineered LLM Attacks
Manohar Kaul, Aditya Saibewar, Sadbhavana Babar
FedImpro: Measuring and Improving Client Update in Federated Learning
Zhenheng Tang, Yonggang Zhang, Shaohuai Shi et al.
Generative Adversarial Equilibrium Solvers
Denizalp Goktas, David Parkes, Ian Gemp et al.
sRGB Real Noise Modeling via Noise-Aware Sampling with Normalizing Flows
Dongjin Kim, Donggoo Jung, Sungyong Baik et al.
One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs
Linbao Li, Yannan Liu, Daojing He et al.
Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model
Chunming He, Chengyu Fang, Yulun Zhang et al.
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu et al.
Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher
Yong Guo, Shulian Zhang, Haolin Pan et al.
Negatively Correlated Ensemble Reinforcement Learning for Online Diverse Game Level Generation
Ziqi Wang, Chengpeng Hu, Jialin Liu et al.
PnP Inversion: Boosting Diffusion-based Editing with 3 Lines of Code
Xuan Ju, Ailing Zeng, Yuxuan Bian et al.
A Unified Theory of Quantum Neural Network Loss Landscapes
Eric Anschuetz
Improved Sampling Algorithms for Lévy-Itô Diffusion Models
Vadim Popov, Assel Yermekova, Tasnima Sadekova et al.
LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts
Hanan Gani, Shariq Bhat, Muzammal Naseer et al.
Counterfactual Realizability
Arvind Raghavan, Elias Bareinboim
Variance-Reducing Couplings for Random Features
Isaac Reid, Stratis Markou, Krzysztof Choromanski et al.
Geometry of Neural Reinforcement Learning in Continuous State and Action Spaces
Saket Tiwari, Omer Gottesman, George D Konidaris
Variance Reduced Halpern Iteration for Finite-Sum Monotone Inclusions
Xufeng Cai, Ahmet Alacaoglu, Jelena Diakonikolas
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
Pengcheng Jiang, Cao (Danica) Xiao, Minhao Jiang et al.
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks
Ivan Rubachev, Nikolay Kartashev, Yury Gorishniy et al.
Federated Orthogonal Training: Mitigating Global Catastrophic Forgetting in Continual Federated Learning
Yavuz Faruk Bakman, Duygu Nur Yaldiz, Yahya Ezzeldin et al.
Fast Value Tracking for Deep Reinforcement Learning
Frank Shih, Faming Liang
An Image Is Worth 1000 Lies: Transferability of Adversarial Images across Prompts on Vision-Language Models
Haochen Luo, Jindong Gu, Fengyuan Liu et al.
MaGIC: Multi-modality Guided Image Completion
Hao Wang, Yongsheng Yu, Tiejian Luo et al.
Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
Jonghyun Lee, Hansam Cho, YoungJoon Yoo et al.
Learning to Discover Regulatory Elements for Gene Expression Prediction
Xingyu Su, Haiyang Yu, Degui Zhi et al.
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang et al.
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
Shikai Fang, Madison Cooley, Da Long et al.
Robustifying and Boosting Training-Free Neural Architecture Search
Zhenfeng He, Yao Shu, Zhongxiang Dai et al.
Unveiling the Pitfalls of Knowledge Editing for Large Language Models
Zhoubo Li, Ningyu Zhang, Yunzhi Yao et al.
FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning
Woosung Koh, Wonbeen Oh, Siyeol Kim et al.
DeepZero: Scaling Up Zeroth-Order Optimization for Deep Model Training
AOCHUAN CHEN, Yimeng Zhang, Jinghan Jia et al.
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
Reza Esfandiarpoor, Stephen Bach
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics
Keyi Shen, Jiangwei Yu, Jose Barreiros et al.
Idempotent Generative Network
Assaf Shocher, Amil Dravid, Yossi Gandelsman et al.
A Newborn Embodied Turing Test for Comparing Object Segmentation Across Animals and Machines
Manju Garimella, Denizhan Pak, Justin Wood et al.
Variance-aware Regret Bounds for Stochastic Contextual Dueling Bandits
Qiwei Di, Tao Jin, Yue Wu et al.
Faithful Vision-Language Interpretation via Concept Bottleneck Models
Songning Lai, Lijie Hu, Junxiao Wang et al.
A Mutual Information Perspective on Federated Contrastive Learning
Christos Louizos, Matthias Reisser, Denis Korzhenkov
Regularization by Texts for Latent Diffusion Inverse Solvers
Jeongsol Kim, Geon Yeong Park, Hyungjin Chung et al.
Partial Gromov-Wasserstein Metric
Yikun Bai, Rocio Diaz Martin, Abihith Kothapalli et al.
SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series
Junyan Cheng, Peter Chin
Transformers can optimally learn regression mixture models
Reese Pathak, Rajat Sen, Weihao Kong et al.
Demystifying the Token Dynamics of Deep Selective State Space Models
Thieu Vo, Duy-Tung Pham, Xin Tong et al.
CLIP-MUSED: CLIP-Guided Multi-Subject Visual Neural Information Semantic Decoding
Qiongyi Zhou, Changde Du, Shengpei Wang et al.
MCM: Masked Cell Modeling for Anomaly Detection in Tabular Data
Jiaxin Yin, Yuanyuan Qiao, Zitang Zhou et al.
Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision
Yaowen Ye, Cassidy Laidlaw, Jacob Steinhardt
VFLAIR: A Research Library and Benchmark for Vertical Federated Learning
TIANYUAN ZOU, Zixuan GU, Yu He et al.
Connect, Collapse, Corrupt: Learning Cross-Modal Tasks with Uni-Modal Data
Yuhui Zhang, Elaine Sui, Serena Yeung
MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures
Anvith Thudi, Chris Maddison
Fast Equilibrium of SGD in Generic Situations
Zhiyuan Li, Yi Wang, Zhiren Wang
Improving Unsupervised Constituency Parsing via Maximizing Semantic Information
Junjie Chen, Xiangheng He, Yusuke Miyao et al.
Large Language Models as Generalizable Policies for Embodied Tasks
Andrew Szot, Max Schwarzer, Harsh Agrawal et al.
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Peizhong Ju, Arnob Ghosh, Ness Shroff
Adversarial Training on Purification (AToP): Advancing Both Robustness and Generalization
Guang Lin, Chao Li, Jianhai Zhang et al.
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert
Expected flow networks in stochastic environments and two-player zero-sum games
Marco Jiralerspong, Bilun Sun, Danilo Vucetic et al.
Efficient Top-m Data Values Identification for Data Selection
Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng et al.
Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models
Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa et al.
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
Anke Tang, Li Shen, Yong Luo et al.
HyperPLR: Hypergraph Generation through Projection, Learning, and Reconstruction
Weihuang Wen, Tianshu Yu
M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model
Kehan Wen, Yutong Hu, Yao Mu et al.
Towards Principled Representation Learning from Videos for Reinforcement Learning
Dipendra Kumar Misra, Akanksha Saran, Tengyang Xie et al.
Towards Best Practices of Activation Patching in Language Models: Metrics and Methods
Fred Zhang, Neel Nanda
Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Parameters for Reasoning
Charlie Snell, Jaehoon Lee, Kelvin Xu et al.
Intermediate Layer Classifiers for OOD generalization
Arnas Uselis, Seong Joon Oh
A Curious Case of the Missing Measure: Better Scores and Worse Generation
Joseph Turian, Jordie Shier
Statistically Optimal $K$-means Clustering via Nonnegative Low-rank Semidefinite Programming
Yubo Zhuang, Xiaohui Chen, Yun Yang et al.
ViSAGe: Video-to-Spatial Audio Generation
Jaeyeon Kim, Heeseung Yun, Gunhee Kim
Deep Kernel Posterior Learning under Infinite Variance Prior Weights
Jorge Loría, Anindya Bhadra
Privacy Auditing of Large Language Models
Ashwinee Panda, Xinyu Tang, Christopher Choquette-Choo et al.
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang et al.
PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos
Alex N. Wang, Christopher Hoang, Yuwen Xiong et al.
AdaMerging: Adaptive Model Merging for Multi-Task Learning
Enneng Yang, Zhenyi Wang, Li Shen et al.
Encoding Unitig-level Assembly Graphs with Heterophilous Constraints for Metagenomic Contigs Binning
Hansheng Xue, Vijini Mallawaarachchi, Lexing Xie et al.
OCEAN: Offline Chain-of-thought Evaluation and Alignment in Large Language Models
Junda Wu, Xintong Li, Ruoyu Wang et al.
Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs
Xuandong Zhao, Lei Li, Yu-Xiang Wang
Breaking Class Barriers: Efficient Dataset Distillation via Inter-Class Feature Compensator
xin zhang, Jiawei Du, Ping Liu et al.
Graph Lottery Ticket Automated
Guibin Zhang, Kun Wang, Wei Huang et al.
Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows
Fangyu Lei, Jixuan Chen, Yuxiao Ye et al.
One For All: Towards Training One Graph Model For All Classification Tasks
Hao Liu, Jiarui Feng, Lecheng Kong et al.
How do we interpret the outputs of a neural network trained on classification?
Yudi Xie
ONLINE EPSILON NET & PIERCING SET FOR GEOMETRIC CONCEPTS
Sujoy Bhore, Devdan Dey, Satyam Singh
SYMBOL: Generating Flexible Black-Box Optimizers through Symbolic Equation Learning
Jiacheng Chen, Zeyuan Ma, Hongshu Guo et al.
Dynamics-Informed Protein Design with Structure Conditioning
Urszula Julia Komorowska, Simon Mathis, Kieran Didi et al.
Xformer: Hybrid X-Shaped Transformer for Image Denoising
Jiale Zhang, Yulun Zhang, Jinjin Gu et al.
Counterfactual Concept Bottleneck Models
Gabriele Dominici, Pietro Barbiero, Francesco Giannini et al.
Predicate Hierarchies Improve Few-Shot State Classification
Emily Jin, Joy Hsu, Jiajun Wu
Learning Multi-Agent Communication with Contrastive Learning
Yat Long (Richie) Lo, Biswa Sengupta, Jakob Foerster et al.
Information Retention via Learning Supplemental Features
Zhipeng Xie, Yahe Li
Towards Neural Scaling Laws for Time Series Foundation Models
Qingren Yao, Chao-Han Huck Yang, Renhe Jiang et al.
AutoVP: An Automated Visual Prompting Framework and Benchmark
Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen et al.
On the Modeling Capabilities of Large Language Models for Sequential Decision Making
Martin Klissarov, R Devon Hjelm, Alexander Toshev et al.
ModuLoRA: Finetuning 2-Bit LLMs on Consumer GPUs by Integrating with Modular Quantizers
Junjie Oscar Yin, Yingheng Wang, Volodymyr Kuleshov et al.
Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency
Qixin ZHANG, Zongqi Wan, Yu Yang et al.
PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
Hangting Ye, Wei Fan, Xiaozhuang Song et al.
Negative Label Guided OOD Detection with Pretrained Vision-Language Models
Xue JIANG, Feng Liu, Zhen Fang et al.
Towards Training Without Depth Limits: Batch Normalization Without Gradient Explosion
Alexandru Meterez, Amir Joudaki, Francesco Orabona et al.
On the Optimization Landscape of Low Rank Adaptation Methods for Large Language Models
Xu-Hui Liu, Yali Du, Jun Wang et al.
Multi-modal Learning: A Look Back and the Road Ahead
Divyam Madaan, Sumit Chopra, Kyunghyun Cho
Correlation and Navigation in the Vocabulary Key Representation Space of Language Models
Letian Peng, Chenyang An, Jingbo Shang
LLMOPT: Learning to Define and Solve General Optimization Problems from Scratch
caigao jiang, Xiang Shu, Hong Qian et al.
SOO-Bench: Benchmarks for Evaluating the Stability of Offline Black-Box Optimization
Hong Qian, Yiyi Zhu, Xiang Shu et al.
Emergent Orientation Maps —— Mechanisms, Coding Efficiency and Robustness
Haixin Zhong, Haoyu Wang, Wei Dai et al.
Learning Partial Graph Matching via Optimal Partial Transport
Gathika Ratnayaka, James Nichols, Qing Wang