Most Cited 2024 "large-scale graph dataset" Papers
12,324 papers found • Page 57 of 62
Conference
REFACTOR: Learning to Extract Theorems from Proofs
Jin Zhou, Yuhuai Wu, Qiyang Li et al.
Transformer Fusion with Optimal Transport
Moritz Imfeld, Jacopo Graldi, Marco Giordano et al.
Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
Fabian Akkerman, Julius Luy, Wouter van Heeswijk et al.
Convolution Meets LoRA: Parameter Efficient Finetuning for Segment Anything Model
Zihan Zhong, Zhiqiang Tang, Tong He et al.
ADOPD: A Large-Scale Document Page Decomposition Dataset
Jiuxiang Gu, Xiangxi Shi, Jason Kuen et al.
To the Cutoff... and Beyond? A Longitudinal Perspective on LLM Data Contamination
Manley Roberts, Himanshu Thakur, Christine Herlihy et al.
P2Seg: Pointly-supervised Segmentation via Mutual Distillation
Zipeng Wang, Xuehui Yu, Xumeng Han et al.
Consciousness-Inspired Spatio-Temporal Abstractions for Better Generalization in Reinforcement Learning
Mingde Zhao, Safa Alver, Harm Seijen et al.
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness
Fran Jelenić, Josip Jukić, Martin Tutek et al.
On Trajectory Augmentations for Off-Policy Evaluation
Ge Gao, Qitong Gao, Xi Yang et al.
Reward-Free Curricula for Training Robust World Models
Marc Rigter, Minqi Jiang, Ingmar Posner
Convergence of Bayesian Bilevel Optimization
Shi Fu, Fengxiang He, Xinmei Tian et al.
Functional Interpolation for Relative Positions improves Long Context Transformers
Shanda Li, Chong You, Guru Guruganesh et al.
Symmetric Single Index Learning
Aaron Zweig, Joan Bruna
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Yehui Tang, Hao Xiong, Nianzu Yang et al.
Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
Hugo Cui, Florent Krzakala, Eric Vanden-Eijnden et al.
Retro-fallback: retrosynthetic planning in an uncertain world
Austin Tripp, Krzysztof Maziarz, Sarah Lewis et al.
TUVF: Learning Generalizable Texture UV Radiance Fields
An-Chieh Cheng, Xueting Li, Sifei Liu et al.
Fast Imitation via Behavior Foundation Models
Matteo Pirotta, Andrea Tirinzoni, Ahmed Touati et al.
MEND: Meta Demonstration Distillation for Efficient and Effective In-Context Learning
Yichuan Li, Xiyao Ma, Sixing Lu et al.
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Aadirupa Saha, Branislav Kveton
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang et al.
Latent 3D Graph Diffusion
Yuning You, Ruida Zhou, Jiwoong Park et al.
State Representation Learning Using an Unbalanced Atlas
Li Meng, Morten Goodwin, Anis Yazidi et al.
Prioritized Soft Q-Decomposition for Lexicographic Reinforcement Learning
Finn Rietz, Erik Schaffernicht, Stefan Heinrich et al.
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
DIPANJYOTI PAUL, Arpita Chowdhury, Xinqi Xiong et al.
Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?
Cheng Han, Qifan Wang, Yiming Cui et al.
Accelerated Sampling with Stacked Restricted Boltzmann Machines
Jorge Fernandez-de-Cossio-Diaz, Clément Roussel, Simona Cocco et al.
BECLR: Batch Enhanced Contrastive Few-Shot Learning
Stylianos Poulakakis-Daktylidis, Hadi Jamali-Rad
DyST: Towards Dynamic Neural Scene Representations on Real-World Videos
Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf et al.
Meta-Learning Priors Using Unrolled Proximal Networks
Yilang Zhang, Georgios B Giannakis
Circumventing Concept Erasure Methods For Text-To-Image Generative Models
Minh Pham, Kelly Marshall, Niv Cohen et al.
Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation
Wenxuan Zhang, Youssef Mohamed, Bernard Ghanem et al.
Diffusion Model for Dense Matching
Jisu Nam, Gyuseong Lee, Seonwoo Kim et al.
Making Retrieval-Augmented Language Models Robust to Irrelevant Context
Ori Yoran, Tomer Wolfson, Ori Ram et al.
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu et al.
Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks through Weight-Sharing in Position-Orientation Space
Erik Bekkers, Sharvaree Vadgama, Rob Hesselink et al.
Most discriminative stimuli for functional cell type clustering
Max F. Burg, Thomas Zenkel, Michaela Vystrčilová et al.
Efficient Backpropagation with Variance Controlled Adaptive Sampling
Ziteng Wang, Jianfei Chen, Jun Zhu
Leveraging augmented-Lagrangian techniques for differentiating over infeasible quadratic programs in machine learning
Antoine Bambade, Fabian Schramm, Adrien Taylor et al.
Conformal Language Modeling
Victor Quach, Adam Fisch, Tal Schuster et al.
Get What You Want, Not What You Don't: Image Content Suppression for Text-to-Image Diffusion Models
Senmao Li, Joost van de Weijer, taihang Hu et al.
Efficient ConvBN Blocks for Transfer Learning and Beyond
Kaichao You, Guo Qin, Anchang Bao et al.
Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
Congpei Qiu, Tong Zhang, Yanhao Wu et al.
RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
Parth Sarthi, Salman Abdullah, Aditi Tuli et al.
Learning Nash Equilibria in Rank-1 Games
Nikolas Patris, Ioannis Panageas
GTMGC: Using Graph Transformer to Predict Molecule’s Ground-State Conformation
Guikun Xu, Yongquan Jiang, PengChuan Lei et al.
Scalable and Effective Implicit Graph Neural Networks on Large Graphs
Juncheng Liu, Bryan Hooi, Kenji Kawaguchi et al.
Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View
HAOYUE DAI, Ignavier Ng, Gongxu Luo et al.
Tangent Transformers for Composition,Privacy and Removal
Tian Yu Liu, Aditya Golatkar, Stefano Soatto
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Shahriar Golchin, Mihai Surdeanu
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
Siyuan Qi, Shuo Chen, Yexin Li et al.
Query-Policy Misalignment in Preference-Based Reinforcement Learning
Xiao Hu, Jianxiong Li, Xianyuan Zhan et al.
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
Ming Jin, Shiyu Wang, Lintao Ma et al.
Accurate Forgetting for Heterogeneous Federated Continual Learning
Abudukelimu Wuerkaixi, Sen Cui, Jingfeng Zhang et al.
EControl: Fast Distributed Optimization with Compression and Error Control
Yuan Gao, Rustem Islamov, Sebastian Stich
Divide and not forget: Ensemble of selectively trained experts in Continual Learning
Grzegorz Rypeść, Sebastian Cygert, Valeriya Khan et al.
VDT: General-purpose Video Diffusion Transformers via Mask Modeling
Haoyu Lu, Guoxing Yang, Nanyi Fei et al.
GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphs
Pengcheng Jiang, Cao Xiao, Adam Cross et al.
Efficient Heterogeneous Meta-Learning via Channel Shuffling Modulation
Minh Hoang, Carl Kingsford
Tag2Text: Guiding Vision-Language Model via Image Tagging
Xinyu Huang, Youcai Zhang, Jinyu Ma et al.
Multi-task Learning with 3D-Aware Regularization
Wei-Hong Li, Steven McDonagh, Ales Leonardis et al.
MixSATGEN: Learning Graph Mixing for SAT Instance Generation
Xinyan Chen, Yang Li, Runzhong Wang et al.
On the Parameterization of Second-Order Optimization Effective towards the Infinite Width
Satoki Ishikawa, Ryo Karakida
Gradual Domain Adaptation via Gradient Flow
Zhan ZHUANG, Yu Zhang, Ying Wei
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Vaidehi Ramesh Patil, Peter Hase, Mohit Bansal
Layer-wise linear mode connectivity
Linara Adilova, Maksym Andriushchenko, Michael Kamp et al.
Decoupling regularization from the action space
Sobhan Mohammadpour, Emma Frejinger, Pierre-Luc Bacon
Learning in reverse causal strategic environments with ramifications on two sided markets
Seamus Somerstep, Yuekai Sun, Yaacov Ritov
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Addressing Signal Delay in Deep Reinforcement Learning
Wei Wang, Dongqi Han, Xufang Luo et al.
Efficient Episodic Memory Utilization of Cooperative Multi-Agent Reinforcement Learning
Hyungho Na, Yunkyeong Seo, Il-chul Moon
Heterogeneous Personalized Federated Learning by Local-Global Updates Mixing via Convergence Rate
Meirui Jiang, Anjie Le, Xiaoxiao Li et al.
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
İlker Kesen, Andrea Pedrotti, Mustafa Dogan et al.
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
Jean-Rémy Conti, Stephan CLEMENCON
Robust Classification via Regression for Learning with Noisy Labels
Erik Englesson, Hossein Azizpour
GNNBoundary: Towards Explaining Graph Neural Networks through the Lens of Decision Boundaries
Xiaoqi Wang, Han Wei Shen
Flag Aggregator: Scalable Distributed Training under Failures and Augmented Losses using Convex Optimization
Hamidreza Almasi, Harsh Mishra, Balajee Vamanan et al.
OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text
Keiran Paster, Marco Dos Santos, Zhangir Azerbayev et al.
Communication-Efficient Federated Non-Linear Bandit Optimization
Chuanhao Li, Chong Liu, Yu-Xiang Wang
Exploring Effective Stimulus Encoding via Vision System Modeling for Visual Prostheses
Chuanqing Wang, Di Wu, Chaoming Fang et al.
Enhancing Human-AI Collaboration Through Logic-Guided Reasoning
Chengzhi Cao, Yinghao Fu, Sheng Xu et al.
Synaptic Weight Distributions Depend on the Geometry of Plasticity
Roman Pogodin, Jonathan Cornford, Arna Ghosh et al.
3D-Aware Hypothesis & Verification for Generalizable Relative Object Pose Estimation
Chen Zhao, Tong Zhang, Mathieu Salzmann
DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
Wenyu Jiang, Hao Cheng, MingCai Chen et al.
Mayfly: a Neural Data Structure for Graph Stream Summarization
yuan feng, Yukun Cao, Hairu Wang et al.
Neural Common Neighbor with Completion for Link Prediction
Xiyuan Wang, Haotong Yang, Muhan Zhang
Masked Completion via Structured Diffusion with White-Box Transformers
Druv Pai, Sam Buchanan, Ziyang Wu et al.
Fine-Tuning Language Models for Factuality
Katherine Tian, Eric Mitchell, Huaxiu Yao et al.
Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
Yuto Nishimura, Taiji Suzuki
DRSM: De-Randomized Smoothing on Malware Classifier Providing Certified Robustness
Shoumik Saha, Wenxiao Wang, Yigitcan Kaya et al.
TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks
Haiyan Jiang, Vincent Zoonekynd, Giulia De Masi et al.
Improved algorithm and bounds for successive projection
Jiashun Jin, Tracy Ke, Gabriel Moryoussef et al.
LILO: Learning Interpretable Libraries by Compressing and Documenting Code
Gabriel Grand, Lio Wong, Maddy Bowers et al.
Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
Hien Dang, Tho-Huu Tran, Tan Nguyen et al.
Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning
Li Ren, Chen Chen, Liqiang Wang et al.
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation
Noel Loo, Ramin Hasani, Mathias Lechner et al.
AmortizedPeriod: Attention-based Amortized Inference for Periodicity Identification
Hang Yu, Cong Liao, Ruolan Liu et al.
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
Jeonghye Kim, Su Young Lee, Woojun Kim et al.
CABINET: Content Relevance-based Noise Reduction for Table Question Answering
Sohan Patnaik, Heril Changwal, Milan Aggarwal et al.
TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting
Defu Cao, Furong Jia, Sercan Arik et al.
Social-Transmotion: Promptable Human Trajectory Prediction
Saeed Saadatnejad, Yang Gao, Kaouther Messaoud et al.
Controlled Text Generation via Language Model Arithmetic
Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner et al.
High Fidelity Neural Audio Compression
Yossi Adi, Gabriel Synnaeve, Jade Copet et al.
Quantifying Language Models' Sensitivity to Spurious Features in Prompt Design or: How I learned to start worrying about prompt formatting
Melanie Sclar, Yejin Choi, Yulia Tsvetkov et al.
PRIME: Prioritizing Interpretability in Failure Mode Extraction
Keivan Rezaei, Mehrdad Saberi, Mazda Moayeri et al.
PoSE: Efficient Context Window Extension of LLMs via Positional Skip-wise Training
Dawei Zhu, Nan Yang, Liang Wang et al.
Data-independent Module-aware Pruning for Hierarchical Vision Transformers
Yang He, Joey Tianyi Zhou
Matryoshka Diffusion Models
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang et al.
SOHES: Self-supervised Open-world Hierarchical Entity Segmentation
Shengcao Cao, Jiuxiang Gu, Jason Kuen et al.
Learning Energy Decompositions for Partial Inference in GFlowNets
Hyosoon Jang, Minsu Kim, Sungsoo Ahn
ImagenHub: Standardizing the evaluation of conditional image generation models
Max Ku, Tianle Li, Kai Zhang et al.
Universal Humanoid Motion Representations for Physics-Based Control
Zhengyi Luo, Jinkun Cao, Josh Merel 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.
Multi-View Causal Representation Learning with Partial Observability
Dingling Yao, Danru Xu, Sébastien Lachapelle et al.
Modelling complex vector drawings with stroke-clouds
Alexander Ashcroft, Ayan Das, Yulia Gryaditskaya et al.
WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
Can Xu, Qingfeng Sun, Kai Zheng et al.
Lagrangian Flow Networks for Conservation Laws
Fabricio Arend Torres, Marcello Negri, Marco Inversi et al.
V-DETR: DETR with Vertex Relative Position Encoding for 3D Object Detection
Yichao Shen, Zigang Geng, YUHUI YUAN et al.
Delta-AI: Local objectives for amortized inference in sparse graphical models
Jean-Pierre Falet, Hae Beom Lee, Nikolay Malkin et al.
Improving Offline RL by Blending Heuristics
Sinong Geng, Aldo Pacchiano, Andrey Kolobov et al.
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive Agents
Jake Grigsby, Jim Fan, Yuke Zhu
Particle Guidance: non-I.I.D. Diverse Sampling with Diffusion Models
Gabriele Corso, Yilun Xu, Valentin De Bortoli et al.
A Cognitive Model for Learning Abstract Relational Structures from Memory-based Decision-Making Tasks
Haruo Hosoya
Diving Segmentation Model into Pixels
Chen Gan, Zihao Yin, Kelei He et al.
Robust Similarity Learning with Difference Alignment Regularization
Shuo Chen, Gang Niu, Chen Gong 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.
LabelDP-Pro: Learning with Label Differential Privacy via Projections
Badih Ghazi, Yangsibo Huang, Pritish Kamath et al.
FLATTEN: optical FLow-guided ATTENtion for consistent text-to-video editing
Yuren Cong, Mengmeng Xu, Christian Simon et al.
Navigating Text-To-Image Customization: From LyCORIS Fine-Tuning to Model Evaluation
Shih-Ying Yeh, Yu-Guan Hsieh, Zhidong Gao et al.
A path-norm toolkit for modern networks: consequences, promises and challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
Rethinking Label Poisoning for GNNs: Pitfalls and Attacks
Vijay Chandra Lingam, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Efficient Score Matching with Deep Equilibrium Layers
Yuhao Huang, Qingsong Wang, Akwum Onwunta et al.
On the Vulnerability of Adversarially Trained Models Against Two-faced Attacks
Shengjie Zhou, Lue Tao, Yuzhou Cao 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.
GraphChef: Decision-Tree Recipes to Explain Graph Neural Networks
Peter Müller, Lukas Faber, Karolis Martinkus et al.
NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization
Gen Li, Lu Yin, Jie Ji et al.
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
Firas Al-Hafez, Guoping Zhao, Jan Peters et al.
Interpreting CLIP's Image Representation via Text-Based Decomposition
Yossi Gandelsman, Alexei Efros, Jacob Steinhardt
Optimal Sample Complexity for Average Reward Markov Decision Processes
Shengbo Wang, Jose Blanchet, Peter Glynn
Space and time continuous physics simulation from partial observations
Steeven Janny, Madiha Nadri, Julie Digne et al.
Learning 3D Particle-based Simulators from RGB-D Videos
William Whitney, Tatiana Lopez-Guevara, Tobias Pfaff et al.
Adaptive Instrument Design for Indirect Experiments
Yash Chandak, Shiv Shankar, Vasilis Syrgkanis et al.
Locality-Aware Graph Rewiring in GNNs
Federico Barbero, Ameya Velingker, Amin Saberi et al.
Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning
Harsh Chaudhari, Giorgio Severi, Alina Oprea et al.
DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$
Allan Jabri, Sjoerd van Steenkiste, Emiel Hoogeboom et al.
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
Yang Liu, Jiashun Cheng, Haihong Zhao et al.
Identifying Representations for Intervention Extrapolation
Sorawit (James) Saengkyongam, Elan Rosenfeld, Pradeep K Ravikumar et al.
Fusion Is Not Enough: Single Modal Attacks on Fusion Models for 3D Object Detection
Zhiyuan Cheng, Hongjun Choi, Shiwei Feng et al.
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset, Edouard Duchesnay, Grigis Antoine et al.
Learning the greatest common divisor: explaining transformer predictions
François Charton
Neural Spectral Methods: Self-supervised learning in the spectral domain
Yiheng Du, Nithin Chalapathi, Aditi Krishnapriyan
RETSim: Resilient and Efficient Text Similarity
Marina Zhang, Owen Vallis, Aysegul Bumin et al.
Beyond IID weights: sparse and low-rank deep Neural Networks are also Gaussian Processes
Thiziri Nait Saada, Alireza Naderi, Jared Tanner
MAMBA: an Effective World Model Approach for Meta-Reinforcement Learning
Zohar Rimon, Tom Jurgenson, Orr Krupnik et al.
Data Distillation Can Be Like Vodka: Distilling More Times For Better Quality
Xuxi Chen, Yu Yang, Zhangyang Wang et al.
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features
Annie Chen, Yoonho Lee, Amrith Setlur et al.
From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
Claudio Battiloro, Indro Spinelli, Lev Telyatinkov et al.
Sample-Efficient Multi-Agent RL: An Optimization Perspective
Nuoya Xiong, Zhihan Liu, Zhaoran Wang et al.
Multimodal Molecular Pretraining via Modality Blending
Qiying Yu, Yudi Zhang, yuyan ni et al.
RAIN: Your Language Models Can Align Themselves without Finetuning
Yuhui Li, Fangyun Wei, Jinjing Zhao et al.
Masks, Signs, And Learning Rate Rewinding
Advait Gadhikar, Rebekka Burkholz
Random Sparse Lifts: Construction, Analysis and Convergence of finite sparse networks
David Robin, Kevin Scaman, marc lelarge
The Human-AI Substitution game: active learning from a strategic labeler
Tom Yan, Chicheng Zhang
On Stationary Point Convergence of PPO-Clip
Ruinan Jin, Shuai Li, Baoxiang Wang
Are Models Biased on Text without Gender-related Language?
Catarina Belém, Preethi Seshadri, Yasaman Razeghi et al.
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Tri Dao
Unveiling Options with Neural Network Decomposition
Mahdi Alikhasi, Levi Lelis
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm
Shurui Gui, Xiner Li, Shuiwang Ji
RingAttention with Blockwise Transformers for Near-Infinite Context
Hao Liu, Matei Zaharia, Pieter Abbeel
SmartPlay : A Benchmark for LLMs as Intelligent Agents
Yue Wu, Xuan Tang, Tom Mitchell et al.
A General Framework for User-Guided Bayesian Optimization
Carl Hvarfner, Frank Hutter, Luigi Nardi
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
Chenguo Lin, Yadong MU
Can Transformers Capture Spatial Relations between Objects?
Chuan Wen, Dinesh Jayaraman, Yang Gao
The LLM Surgeon
Tycho van der Ouderaa, Markus Nagel, Mart van Baalen et al.
Predictive, scalable and interpretable knowledge tracing on structured domains
Hanqi Zhou, Robert Bamler, Charley Wu et al.
Imitation Learning from Observation with Automatic Discount Scheduling
Yuyang Liu, Weijun Dong, Yingdong Hu et al.
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
Yuan Gao, WEIZHONG ZHANG, Wenhan Luo et al.
Language Model Self-improvement by Reinforcement Learning Contemplation
Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li et al.
Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning
Chengxing Jia, Chen-Xiao Gao, Hao Yin et al.
Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction
Yilan Zhang, Yingxue XU, Jianqi Chen et al.
On the Role of General Function Approximation in Offline Reinforcement Learning
Chenjie Mao, Qiaosheng Zhang, Zhen Wang et al.
Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning
Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng et al.
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra
Retrieval-Enhanced Contrastive Vision-Text Models
Ahmet Iscen, Mathilde Caron, Alireza Fathi et al.
Function Vectors in Large Language Models
Eric Todd, Millicent Li, Arnab Sen Sharma et al.
Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization
Yang Jin, Kun Xu, Kun Xu et al.
LEGO-Prover: Neural Theorem Proving with Growing Libraries
Haiming Wang, Huajian Xin, Chuanyang Zheng et al.
GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher
Youliang Yuan, Wenxiang Jiao, Wenxuan Wang et al.
DiffEnc: Variational Diffusion with a Learned Encoder
Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi et al.
GIM: Learning Generalizable Image Matcher From Internet Videos
Xuelun Shen, zhipeng cai, Wei Yin et al.
Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection
Xiangyu Dong, Xingyi Zhang, Sibo WANG
DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning
Jing Xiong, Zixuan Li, Chuanyang Zheng et al.
In-context Autoencoder for Context Compression in a Large Language Model
Tao Ge, Hu Jing, Lei Wang et al.
Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression
Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk et al.
ZipIt! Merging Models from Different Tasks without Training
George Stoica, Daniel Bolya, Jakob Bjorner et al.
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
Yuxin Zhang, Lirui Zhao, Mingbao Lin et al.
RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment
Kevin Yang, Dan Klein, Asli Celikyilmaz et al.
Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
Hongbin Huang, Minghua Chen, Xiao Qiao
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart et al.