Most Cited ICML "spatiotemporal dependencies" Papers
5,975 papers found • Page 2 of 30
Conference
SparQ Attention: Bandwidth-Efficient LLM Inference
Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley et al.
Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning
Zhenni Bi, Kai Han, Chuanjian Liu et al.
MaxMin-RLHF: Alignment with Diverse Human Preferences
Souradip Chakraborty, Jiahao Qiu, Hui Yuan et al.
MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions
Kai Zhang, Yi Luan, Hexiang Hu et al.
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning
Hao Zhao, Maksym Andriushchenko, Francesco Croce et al.
Audio Flamingo 2: An Audio-Language Model with Long-Audio Understanding and Expert Reasoning Abilities
Sreyan Ghosh, Zhifeng Kong, Sonal Kumar et al.
Human Alignment of Large Language Models through Online Preference Optimisation
Daniele Calandriello, Zhaohan Guo, REMI MUNOS et al.
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models
Christian Schlarmann, Naman Singh, Francesco Croce et al.
Representation Surgery for Multi-Task Model Merging
Enneng Yang, Li Shen, Zhenyi Wang et al.
IM-3D: Iterative Multiview Diffusion and Reconstruction for High-Quality 3D Generation
Luke Melas-Kyriazi, Iro Laina, Christian Rupprecht et al.
FlowMM: Generating Materials with Riemannian Flow Matching
Benjamin Kurt Miller, Ricky T. Q. Chen, Anuroop Sriram et al.
Language Models with Conformal Factuality Guarantees
Christopher Mohri, Tatsunori Hashimoto
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta et al.
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
YU DU, Fangyun Wei, Hongyang Zhang
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
Anke Tang, Li Shen, Yong Luo et al.
Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers
Katherine Crowson, Stefan Baumann, Alex Birch et al.
Plan-and-Act: Improving Planning of Agents for Long-Horizon Tasks
Lutfi Erdogan, Hiroki Furuta, Sehoon Kim et al.
Robust Classification via a Single Diffusion Model
Huanran Chen, Yinpeng Dong, Zhengyi Wang et al.
TabICL: A Tabular Foundation Model for In-Context Learning on Large Data
Jingang QU, David Holzmüller, Gael Varoquaux et al.
Evaluating Quantized Large Language Models
Shiyao Li, Xuefei Ning, Luning Wang et al.
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code
ziniu hu, Ahmet Iscen, Aashi Jain et al.
Multi-agent Architecture Search via Agentic Supernet
Guibin Zhang, Luyang Niu, Junfeng Fang et al.
In-Context Language Learning: Architectures and Algorithms
Ekin Akyürek, Bailin Wang, Yoon Kim et al.
A Closer Look at the Limitations of Instruction Tuning
Sreyan Ghosh, Chandra Kiran Evuru, Sonal Kumar et al.
Guiding LLMs The Right Way: Fast, Non-Invasive Constrained Generation
Luca Beurer-Kellner, Marc Fischer, Martin Vechev
Boximator: Generating Rich and Controllable Motions for Video Synthesis
Jiawei Wang, Yuchen Zhang, Jiaxin Zou et al.
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization
Yang Jin, Zhicheng Sun, Kun Xu et al.
DS-Agent: Automated Data Science by Empowering Large Language Models with Case-Based Reasoning
Siyuan Guo, Cheng Deng, Ying Wen et al.
Low-Cost High-Power Membership Inference Attacks
Sajjad Zarifzadeh, Philippe Liu, Reza Shokri
Position: Graph Foundation Models Are Already Here
Haitao Mao, Zhikai Chen, Wenzhuo Tang et al.
Get More with LESS: Synthesizing Recurrence with KV Cache Compression for Efficient LLM Inference
Harry Dong, Xinyu Yang, Zhenyu Zhang et al.
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations
Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.
Wukong: Towards a Scaling Law for Large-Scale Recommendation
Buyun Zhang, Liang Luo, Yuxin Chen et al.
NExT-Chat: An LMM for Chat, Detection and Segmentation
Ao Zhang, Yuan Yao, Wei Ji et al.
A Dynamical Model of Neural Scaling Laws
Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan
Reward-Guided Speculative Decoding for Efficient LLM Reasoning
Baohao Liao, Yuhui Xu, Hanze Dong et al.
FiT: Flexible Vision Transformer for Diffusion Model
Zeyu Lu, ZiDong Wang, Di Huang et al.
Sundial: A Family of Highly Capable Time Series Foundation Models
Yong Liu, Guo Qin, Zhiyuan Shi et al.
video-SALMONN: Speech-Enhanced Audio-Visual Large Language Models
Guangzhi Sun, Wenyi Yu, Changli Tang et al.
Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation
Fanqing Meng, Jiaqi Liao, Xinyu Tan et al.
Rolling Diffusion Models
David Ruhe, Jonathan Heek, Tim Salimans et al.
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
Federico Bianchi, Patrick John Chia, Mert Yuksekgonul et al.
Cradle: Empowering Foundation Agents towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu et al.
History-Guided Video Diffusion
Kiwhan Song, Boyuan Chen, Max Simchowitz et al.
D-Flow: Differentiating through Flows for Controlled Generation
Heli Ben-Hamu, Omri Puny, Itai Gat et al.
Watermark Stealing in Large Language Models
Nikola Jovanović, Robin Staab, Martin Vechev
Diffusion Adversarial Post-Training for One-Step Video Generation
Shanchuan Lin, Xin Xia, Yuxi Ren et al.
Accurate LoRA-Finetuning Quantization of LLMs via Information Retention
Haotong Qin, Xudong Ma, Xingyu Zheng et al.
A Touch, Vision, and Language Dataset for Multimodal Alignment
Letian Fu, Gaurav Datta, Huang Huang et al.
DITTO: Diffusion Inference-Time T-Optimization for Music Generation
Zachary Novack, Julian McAuley, Taylor Berg-Kirkpatrick et al.
Stay on Topic with Classifier-Free Guidance
Guillaume Sanchez, Alexander Spangher, Honglu Fan et al.
Guidance with Spherical Gaussian Constraint for Conditional Diffusion
Lingxiao Yang, Shutong Ding, Yifan Cai et al.
SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks
Jiwon Song, Kyungseok Oh, Taesu Kim et al.
DE-COP: Detecting Copyrighted Content in Language Models Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
VideoPrism: A Foundational Visual Encoder for Video Understanding
Long Zhao, Nitesh Bharadwaj Gundavarapu, Liangzhe Yuan et al.
Scaling Test-Time Compute Without Verification or RL is Suboptimal
Amrith Setlur, Nived Rajaraman, Sergey Levine et al.
DistiLLM: Towards Streamlined Distillation for Large Language Models
Jongwoo Ko, Sungnyun Kim, Tianyi Chen et al.
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Hellsten, Luigi Nardi
Fast Adversarial Attacks on Language Models In One GPU Minute
Vinu Sankar Sadasivan, Shoumik Saha, Gaurang Sriramanan et al.
Training Deep Learning Models with Norm-Constrained LMOs
Thomas Pethick, Wanyun Xie, Kimon Antonakopoulos et al.
WAVES: Benchmarking the Robustness of Image Watermarks
Bang An, Mucong Ding, Tahseen Rabbani et al.
XAttention: Block Sparse Attention with Antidiagonal Scoring
Ruyi Xu, Guangxuan Xiao, Haofeng Huang et al.
Learning to Model the World With Language
Jessy Lin, Yuqing Du, Olivia Watkins et al.
Moirai-MoE: Empowering Time Series Foundation Models with Sparse Mixture of Experts
Xu Liu, Juncheng Liu, Gerald Woo et al.
DiffDA: a Diffusion model for weather-scale Data Assimilation
Langwen Huang, Lukas Gianinazzi, Yuejiang Yu et al.
InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining
Boxin Wang, Wei Ping, Lawrence McAfee et al.
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov et al.
Learning a Diffusion Model Policy from Rewards via Q-Score Matching
Michael Psenka, Alejandro Escontrela, Pieter Abbeel et al.
GuardAgent: Safeguard LLM Agents via Knowledge-Enabled Reasoning
Zhen Xiang, Linzhi Zheng, Yanjie Li et al.
DOGE: Domain Reweighting with Generalization Estimation
Simin Fan, Matteo Pagliardini, Martin Jaggi
VoroNav: Voronoi-based Zero-shot Object Navigation with Large Language Model
Pengying Wu, Yao Mu, Bingxian Wu et al.
HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation
Tianwei Lin, Wenqiao Zhang, Sijing Li et al.
What If We Recaption Billions of Web Images with LLaMA-3?
Xianhang Li, Haoqin Tu, Mude Hui et al.
Stochastic Interpolants with Data-Dependent Couplings
Michael Albergo, Mark Goldstein, Nicholas Boffi et al.
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
Zhenyu Hou, Xin Lv, Rui Lu et al.
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
Hila Chefer, Uriel Singer, Amit Zohar et al.
Asymmetry in Low-Rank Adapters of Foundation Models
Jiacheng Zhu, Kristjan Greenewald, Kimia Nadjahi et al.
Image Fusion via Vision-Language Model
Zixiang Zhao, Lilun Deng, Haowen Bai et al.
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models
Marwa Abdulhai, Isadora White, Charlie Snell et al.
LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery
Pingchuan Ma, Johnson Tsun-Hsuan Wang, Minghao Guo et al.
RigorLLM: Resilient Guardrails for Large Language Models against Undesired Content
Zhuowen Yuan, Zidi Xiong, Yi Zeng et al.
SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?
Samuel Miserendino, Michele Wang, Tejal Patwardhan et al.
SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization
Jintao Zhang, Haofeng Huang, Pengle Zhang et al.
Long-Tail Learning with Foundation Model: Heavy Fine-Tuning Hurts
Jiang-Xin Shi, Tong Wei, Zhi Zhou et al.
Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning
Sungwon Han, Jinsung Yoon, Sercan Arik et al.
Repoformer: Selective Retrieval for Repository-Level Code Completion
Di Wu, Wasi Ahmad, Dejiao Zhang et al.
ShadowKV: KV Cache in Shadows for High-Throughput Long-Context LLM Inference
Hanshi Sun, Li-Wen Chang, Wenlei Bao et al.
GliDe with a CaPE: A Low-Hassle Method to Accelerate Speculative Decoding
Cunxiao Du, Jing Jiang, Xu Yuanchen et al.
NExT: Teaching Large Language Models to Reason about Code Execution
Ansong Ni, Miltiadis Allamanis, Arman Cohan et al.
Inductive Moment Matching
Linqi (Alex) Zhou, Stefano Ermon, Jiaming Song
Flow Q-Learning
Seohong Park, Qiyang Li, Sergey Levine
RE-Bench: Evaluating Frontier AI R&D Capabilities of Language Model Agents against Human Experts
Hjalmar Wijk, Tao Lin, Joel Becker et al.
Dense Reward for Free in Reinforcement Learning from Human Feedback
Alexander Chan, Hao Sun, Samuel Holt et al.
Covert Malicious Finetuning: Challenges in Safeguarding LLM Adaptation
Danny Halawi, Alexander Wei, Eric Wallace et al.
Mixtures of Experts Unlock Parameter Scaling for Deep RL
Johan Obando Ceron, Ghada Sokar, Timon Willi 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.
Prompt-tuning Latent Diffusion Models for Inverse Problems
Hyungjin Chung, Jong Chul YE, Peyman Milanfar et al.
Fast Video Generation with Sliding Tile Attention
Peiyuan Zhang, Yongqi Chen, Runlong Su et al.
Should we be going MAD? A Look at Multi-Agent Debate Strategies for LLMs
Andries Smit, Nathan Grinsztajn, Paul Duckworth et al.
MMPareto: Boosting Multimodal Learning with Innocent Unimodal Assistance
Yake Wei, Di Hu
An analytic theory of creativity in convolutional diffusion models
Mason Kamb, Surya Ganguli
DoraemonGPT: Toward Understanding Dynamic Scenes with Large Language Models (Exemplified as A Video Agent)
Zongxin Yang, Guikun Chen, Xiaodi Li et al.
KernelBench: Can LLMs Write Efficient GPU Kernels?
Anne Ouyang, Simon Guo, Simran Arora et al.
MM-RLHF: The Next Step Forward in Multimodal LLM Alignment
Yi-Fan Zhang, Tao Yu, Haochen Tian et al.
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
Kaixuan Huang, Jiacheng Guo, Zihao Li et al.
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
Xiang Cheng, Yuxin Chen, Suvrit Sra
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs et al.
Position: Topological Deep Learning is the New Frontier for Relational Learning
Theodore Papamarkou, Tolga Birdal, Michael Bronstein et al.
OptiMUS: Scalable Optimization Modeling with (MI)LP Solvers and Large Language Models
Ali AhmadiTeshnizi, Wenzhi Gao, Madeleine Udell
Getting the most out of your tokenizer for pre-training and domain adaptation
Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Michael Matthews, Michael Beukman, Benjamin Ellis et al.
Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling
Guoqi Yu, Jing Zou, Xiaowei Hu et al.
All-in-one simulation-based inference
Manuel Gloeckler, Michael Deistler, Christian Weilbach et al.
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
Automatically Interpreting Millions of Features in Large Language Models
Gonçalo Paulo, Alex Mallen, Caden Juang et al.
Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement
che liu, Zhongwei Wan, Cheng Ouyang et al.
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
Zhen Qin, Daoyuan Chen, Bingchen Qian et al.
Test-Time Model Adaptation with Only Forward Passes
Shuaicheng Niu, Chunyan Miao, Guohao Chen et al.
Training-Free Long-Context Scaling of Large Language Models
Chenxin An, Fei Huang, Jun Zhang et al.
Transformers, parallel computation, and logarithmic depth
Clayton Sanford, Daniel Hsu, Matus Telgarsky
EE-LLM: Large-Scale Training and Inference of Early-Exit Large Language Models with 3D Parallelism
Yanxi Chen, Xuchen Pan, Yaliang Li et al.
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla et al.
Position: The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning
Micah Goldblum, Marc Finzi, Keefer Rowan et al.
Parameter-Efficient Fine-Tuning with Discrete Fourier Transform
Ziqi Gao, Qichao Wang, Aochuan Chen et al.
Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge
Swarnadeep Saha, Xian Li, Marjan Ghazvininejad et al.
AutoML-Agent: A Multi-Agent LLM Framework for Full-Pipeline AutoML
Patara Trirat, Wonyong Jeong, Sung Ju Hwang
Feedback Loops With Language Models Drive In-Context Reward Hacking
Alexander Pan, Erik Jones, Meena Jagadeesan et al.
Decoding-time Realignment of Language Models
Tianlin Liu, Shangmin Guo, Leonardo Martins Bianco et al.
Normalizing Flows are Capable Generative Models
Shuangfei Zhai, Ruixiang Zhang, Preetum Nakkiran et al.
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion
Hila Manor, Tomer Michaeli
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models
Lichang Chen, Jiuhai Chen, Tom Goldstein et al.
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
Jianan Zhou, Zhiguang Cao, Yaoxin Wu et al.
Foundation Policies with Hilbert Representations
Seohong Park, Tobias Kreiman, Sergey Levine
Learning Multi-Level Features with Matryoshka Sparse Autoencoders
Bart Bussmann, Noa Nabeshima, Adam Karvonen et al.
Towards Modular LLMs by Building and Reusing a Library of LoRAs
Oleksiy Ostapenko, Zhan Su, Edoardo Ponti et al.
CLLMs: Consistency Large Language Models
Siqi Kou, Lanxiang Hu, Zhezhi He et al.
SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
Adam Karvonen, Can Rager, Johnny Lin et al.
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
Zhiheng Xi, Wenxiang Chen, Boyang Hong et al.
On the Origins of Linear Representations in Large Language Models
Yibo Jiang, Goutham Rajendran, Pradeep Ravikumar et al.
CogBench: a large language model walks into a psychology lab
Julian Coda-Forno, Marcel Binz, Jane Wang et al.
Learning to Route Among Specialized Experts for Zero-Shot Generalization
Mohammed Muqeeth, Haokun Liu, Yufan Liu et al.
NoLiMa: Long-Context Evaluation Beyond Literal Matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt et al.
VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters
Mouxiang Chen, Lefei Shen, Zhuo Li et al.
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance et al.
SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention
Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.
Position: What Can Large Language Models Tell Us about Time Series Analysis
Ming Jin, Yi-Fan Zhang, Wei Chen et al.
CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents
Qinlin Zhao, Jindong Wang, Yixuan Zhang et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Josh Engels, Senthooran Rajamanoharan et al.
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo
Stephen Zhao, Rob Brekelmans, Alireza Makhzani et al.
Neural Operators with Localized Integral and Differential Kernels
Miguel Liu-Schiaffini, Julius Berner, Boris Bonev et al.
Instruction Tuning for Secure Code Generation
Jingxuan He, Mark Vero, Gabriela Krasnopolska et al.
Dynamic Evaluation of Large Language Models by Meta Probing Agents
Kaijie Zhu, Jindong Wang, Qinlin Zhao et al.
Auto-Regressive Next-Token Predictors are Universal Learners
Eran Malach
Adaptive Text Watermark for Large Language Models
Yepeng Liu, Yuheng Bu
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Keke Huang, Yu Guang Wang, Ming Li et al.
Differentially Private Bias-Term Fine-tuning of Foundation Models
Zhiqi Bu, Yu-Xiang Wang, Sheng Zha et al.
Swallowing the Bitter Pill: Simplified Scalable Conformer Generation
Yuyang Wang, Ahmed Elhag, Navdeep Jaitly et al.
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
Junhong Shen, Neil Tenenholtz, James Hall et al.
Pruner-Zero: Evolving Symbolic Pruning Metric From Scratch for Large Language Models
Peijie Dong, Lujun Li, Zhenheng Tang et al.
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara McAllister, Amar Phanishayee et al.
Organize the Web: Constructing Domains Enhances Pre-Training Data Curation
Alexander Wettig, Kyle Lo, Sewon Min et al.
Mechanistic Design and Scaling of Hybrid Architectures
Michael Poli, Armin Thomas, Eric Nguyen et al.
Long-Term TalkingFace Generation via Motion-Prior Conditional Diffusion Model
SHEN FEI, Cong Wang, Junyao Gao et al.
A Diffusion Model Framework for Unsupervised Neural Combinatorial Optimization
Sebastian Sanokowski, Sepp Hochreiter, Sebastian Lehner
AquaLoRA: Toward White-box Protection for Customized Stable Diffusion Models via Watermark LoRA
Weitao Feng, Wenbo Zhou, Jiyan He et al.
Particle Denoising Diffusion Sampler
Angus Phillips, Hai-Dang Dau, Michael Hutchinson et al.
MolCRAFT: Structure-Based Drug Design in Continuous Parameter Space
Yanru Qu, Keyue Qiu, Yuxuan Song et al.
Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
Andy (DiJia) Su, Hanlin Zhu, Yingchen Xu et al.
Premise Order Matters in Reasoning with Large Language Models
Xinyun Chen, Ryan Chi, Xuezhi Wang et al.
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models
Louis Sharrock, Jack Simons, Song Liu et al.
Cooperative Graph Neural Networks
Ben Finkelshtein, Xingyue Huang, Michael Bronstein et al.
Masked Autoencoders Are Effective Tokenizers for Diffusion Models
Hao Chen, Yujin Han, Fangyi Chen et al.
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han et al.
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
Guibin Zhang, Yanwei Yue, Xiangguo Sun et al.
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Theodoros Kouzelis, Ioannis Kakogeorgiou, Spyros Gidaris et al.
Scaling Exponents Across Parameterizations and Optimizers
Katie Everett, Lechao Xiao, Mitchell Wortsman et al.
NETS: A Non-equilibrium Transport Sampler
Michael Albergo, Eric Vanden-Eijnden
Curated LLM: Synergy of LLMs and Data Curation for tabular augmentation in low-data regimes
Nabeel Seedat, Nicolas Huynh, Boris van Breugel et al.
FlexTok: Resampling Images into 1D Token Sequences of Flexible Length
Roman Bachmann, Jesse Allardice, David Mizrahi et al.
SelfIE: Self-Interpretation of Large Language Model Embeddings
Haozhe Chen, Carl Vondrick, Chengzhi Mao
Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM’s Reasoning Capability
Zicheng Lin, Tian Liang, Jiahao Xu et al.
All-atom Diffusion Transformers: Unified generative modelling of molecules and materials
Chaitanya Joshi, Xiang Fu, Yi-Lun Liao et al.
Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
Zhi Zheng, Zhuoliang Xie, Zhenkun Wang et al.
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models
YAN WANG, Lihao Wang, Yuning Shen et al.
ReFocus: Visual Editing as a Chain of Thought for Structured Image Understanding
Xingyu Fu, Minqian Liu, Zhengyuan Yang et al.
Causal Representation Learning from Multiple Distributions: A General Setting
Kun Zhang, Shaoan Xie, Ignavier Ng et al.
EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers
Daiheng Gao, Shilin Lu, Wenbo Zhou et al.
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Junyuan Hong, Jinhao Duan, Chenhui Zhang et al.
Why Larger Language Models Do In-context Learning Differently?
Zhenmei Shi, Junyi Wei, Zhuoyan Xu et al.
RoSA: Accurate Parameter-Efficient Fine-Tuning via Robust Adaptation
Mahdi Nikdan, Soroush Tabesh, Elvir Crnčević et al.
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Banghua Zhu, Michael Jordan, Jiantao Jiao
Self-Alignment of Large Language Models via Monopolylogue-based Social Scene Simulation
Xianghe Pang, shuo tang, Rui Ye et al.
Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models
Didi Zhu, Zhongyi Sun, Zexi Li et al.
Linguistic Calibration of Long-Form Generations
Neil Band, Xuechen Li, Tengyu Ma et al.
Antidote: Post-fine-tuning Safety Alignment for Large Language Models against Harmful Fine-tuning Attack
Tiansheng Huang, Gautam Bhattacharya, Pratik Joshi et al.
STAIR: Improving Safety Alignment with Introspective Reasoning
Yichi Zhang, Siyuan Zhang, Yao Huang et al.
FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching
Sucheng Ren, Qihang Yu, Ju He et al.
Variational Learning is Effective for Large Deep Networks
Yuesong Shen, Nico Daheim, Bai Cong et al.
FlipAttack: Jailbreak LLMs via Flipping
Yue Liu, Xiaoxin He, Miao Xiong et al.
Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration
Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.