Most Cited 2025 "post-training llms" Papers

SIMPL: Scalable and hassle-free optimisation of neural representations from behaviour

Tom George, Pierre Glaser, Kimberly Stachenfeld et al.

Building Blocks of Differentially Private Training

Mahmoud Hegazy, Aymeric Dieuleveut

Federated Few-Shot Class-Incremental Learning

Muhammad Anwar Masum, Mahardhika Pratama, Lin Liu et al.

Vision and Language Synergy for Rehearsal Free Continual Learning

Muhammad Anwar Masum, Mahardhika Pratama, Savitha Ramasamy et al.

RESuM: A Rare Event Surrogate Model for Physics Detector Design

Ann-Kathrin Schuetz, Alan Poon, Aobo Li

Mutual Effort for Efficiency: A Similarity-based Token Pruning for Vision Transformers in Self-Supervised Learning

Sheng Li, Qitao Tan, Yue Dai et al.

Minimalistic Predictions for Online Class Constraint Scheduling

Dorian Guyot, Alexandra Lassota

XAIguiFormer: explainable artificial intelligence guided transformer for brain disorder identification

Hanning Guo, Farah Abdellatif, Yu Fu et al.

Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks

Hanling Tian, Yuhang Liu, Mingzhen He et al.

GDrag:Towards General-Purpose Interactive Editing with Anti-ambiguity Point Diffusion

Xiaojian Lin, Hanhui Li, Yuhao Cheng et al.

Mechanistic Interpretability Meets Vision Language Models: Insights and Limitations

Yiming Liu, Yuhui Zhang, Serena Yeung

Recovery of Causal Graph Involving Latent Variables via Homologous Surrogates

Xiuchuan Li, Jun Wang, Tongliang Liu

Mastering Task Arithmetic: $\tau$Jp as a Key Indicator for Weight Disentanglement

Kotaro Yoshida, Yuji Naraki, Takafumi Horie et al.

SFS: Smarter Code Space Search improves LLM Inference Scaling

Jonathan Light, Yue Wu, Yiyou Sun et al.

YOLO-RD: Introducing Relevant and Compact Explicit Knowledge to YOLO by Retriever-Dictionary

Hao-Tang Tsui, Chien-Yao Wang, Hong-Yuan Liao

How much of my dataset did you use? Quantitative Data Usage Inference in Machine Learning

Yao Tong, Jiayuan Ye, Sajjad Zarifzadeh et al.

StringLLM: Understanding the String Processing Capability of Large Language Models

Xilong Wang, Hao Fu, Jindong Wang et al.

Factual Context Validation and Simplification: A Scalable Method to Enhance GPT Trustworthiness and Efficiency

Tianyi Huang

Support is All You Need for Certified VAE Training

Changming Xu, Debangshu Banerjee, Deepak Vasisht et al.

Scaling In-the-Wild Training for Diffusion-based Illumination Harmonization and Editing by Imposing Consistent Light Transport

Lvmin Zhang, Anyi Rao, Maneesh Agrawala

Sparse components distinguish visual pathways & their alignment to neural networks

Ammar I Marvi, Nancy Kanwisher, Meenakshi Khosla

GaussianAnything: Interactive Point Cloud Flow Matching for 3D Generation

Yushi LAN, Shangchen Zhou, Zhaoyang Lyu et al.

Identifying latent state transitions in non-linear dynamical systems

Çağlar Hızlı, Çağatay Yıldız, Matthias Bethge 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

Bayesian Image Regression with Soft-thresholded Conditional Autoregressive Prior

Yuliang Xu, Jian Kang

Linear Recurrences Accessible to Everyone

Felix Sarnthein

The Ramanujan Library - Automated Discovery on the Hypergraph of Integer Relations

Itay Beit Halachmi, Ido Kaminer

More Experts Than Galaxies: Conditionally-Overlapping Experts with Biologically-Inspired Fixed Routing

Sagi Shaier, Francisco Pereira, Katharina Kann et al.

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

Scalable Extraction of Training Data from Aligned, Production Language Models

Milad Nasr, Javier Rando, Nicholas Carlini et al.

Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher

Yong Guo, Shulian Zhang, Haolin Pan et al.

Bias Mitigation in Graph Diffusion Models

Meng Yu, Kun Zhan

Improved Sampling Algorithms for Lévy-Itô Diffusion Models

Vadim Popov, Assel Yermekova, Tasnima Sadekova et al.

MMD-Regularized Unbalanced Optimal Transport

SakethaNath Jagarlapudi, Pratik Jawanpuria, Piyushi Manupriya

Do vision models perceive objects like toddlers ?

Arthur Aubret, Jochen Triesch

Relation-Aware Diffusion for Heterogeneous Graphs with Partially Observed Features

Daeho Um, Yoonji Lee, Jiwoong Park et al.

MA$^2$E: Addressing Partial Observability in Multi-Agent Reinforcement Learning with Masked Auto-Encoder

Sehyeok Kang, Yongsik Lee, Gahee Kim et al.

Rapid Selection and Ordering of In-Context Demonstrations via Prompt Embedding Clustering

Kha Pham, Hung Le, Man Ngo et al.

Plug, Play, and Generalize: Length Extrapolation with Pointer-Augmented Neural Memory

Svetha Venkatesh, Kien Do, Hung Le et al.

FlickerFusion: Intra-trajectory Domain Generalizing Multi-agent Reinforcement Learning

Woosung Koh, Wonbeen Oh, Siyeol Kim et al.

A deep inverse-mapping model for a flapping robotic wing

Hadar Sharvit, Raz Karl, Tsevi Beatus

Robust Transfer of Safety-Constrained Reinforcement Learning Agents

Markel Zubia, Thiago Simão, Nils Jansen

Mind the GAP: Glimpse-based Active Perception improves generalization and sample efficiency of visual reasoning

Oleh Kolner, Thomas Ortner, Stanisław Woźniak et al.

Brain Bandit: A Biologically Grounded Neural Network for Efficient Control of Exploration

Chen Jiang, Jiahui An, Yating Liu et al.

Differential Transformer

Tianzhu Ye, Li Dong, Yuqing Xia et al.

Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation

Yikun Zhang, Geyan Ye, Chaohao Yuan et al.

Retri3D: 3D Neural Graphics Representation Retrieval

Yushi Guan, Daniel Kwan, Jean Dandurand et al.

Improving Unsupervised Constituency Parsing via Maximizing Semantic Information

Junjie Chen, Xiangheng He, Yusuke Miyao et al.

Cross-Domain Off-Policy Evaluation and Learning for Contextual Bandits

Yuta Natsubori, Masataka Ushiku, Yuta Saito

Efficient Top-m Data Values Identification for Data Selection

Xiaoqiang Lin, Xinyi Xu, See-Kiong Ng et al.

Learning to Search from Demonstration Sequences

Dixant Mittal, Liwei Kang, Wee Sun Lee

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models

Yong-Hyun Park, Chieh-Hsin Lai, Satoshi Hayakawa et al.

HyperPLR: Hypergraph Generation through Projection, Learning, and Reconstruction

Weihuang Wen, Tianshu Yu

Semi-Parametric Retrieval via Binary Bag-of-Tokens Index

Jiawei Zhou, Li Dong, Furu Wei et al.

M^3PC: Test-time Model Predictive Control using Pretrained Masked Trajectory Model

Kehan Wen, Yutong Hu, Yao Mu et al.

Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space

Zhiliang Chen, Xinyuan Niu, Chuan Sheng Foo et al.

Scaling LLM Test-Time Compute Optimally Can be More Effective than Scaling Parameters for Reasoning

Charlie Snell, Jaehoon Lee, Kelvin Xu et al.

Jamba: Hybrid Transformer-Mamba Language Models

Barak Lenz, Opher Lieber, Alan Arazi et al.

A Curious Case of the Missing Measure: Better Scores and Worse Generation

Joseph Turian, Jordie Shier

Deep Kernel Posterior Learning under Infinite Variance Prior Weights

Jorge Loría, Anindya Bhadra

Credit-based self organizing maps: training deep topographic networks with minimal performance degradation

Amir Ozhan Dehghani, Xinyu Qian, Asa Farahani et al.

TexTailor: Customized Text-aligned Texturing via Effective Resampling

Suin Lee, DAE SHIK KIM

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

PPT: Patch Order Do Matters In Time Series Pretext Task

Jaeho Kim, Kwangryeol Park, Sukmin Yun et al.

Towards Unbiased Learning in Semi-Supervised Semantic Segmentation

Rui Sun, Huayu Mai, Wangkai Li et al.

Chain-of-Focus Prompting: Leveraging Sequential Visual Cues to Prompt Large Autoregressive Vision Models

Jiyang Zheng, Jialiang Shen, Yu Yao 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

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.

Do not write that jailbreak paper

Javier Rando

It Helps to Take a Second Opinion: Teaching Smaller LLMs To Deliberate Mutually via Selective Rationale Optimisation

Sohan Patnaik, Milan Aggarwal, Sumit Bhatia et al.

Learning Partial Graph Matching via Optimal Partial Transport

Gathika Ratnayaka, James Nichols, Qing Wang

MTSAM: Multi-Task Fine-Tuning for Segment Anything Model

Xuehao Wang, Zhan ZHUANG, Feiyang YE et al.

HeadMap: Locating and Enhancing Knowledge Circuits in LLMs

Xuehao Wang, Liyuan Wang, Binghuai Lin et al.

Learning to Explore and Exploit with GNNs for Unsupervised Combinatorial Optimization

Utku Umur Acikalin, Aaron Ferber, Carla Gomes

Modeling Unseen Environments with Language-guided Composable Causal Components in Reinforcement Learning

Xinyue Wang, Biwei Huang

HiRA: Parameter-Efficient Hadamard High-Rank Adaptation for Large Language Models

Qiushi Huang, Tom Ko, Zhan ZHUANG et al.

Long-Short Decision Transformer: Bridging Global and Local Dependencies for Generalized Decision-Making

Jincheng Wang, Penny Karanasou, Pengyuan Wei et al.

Joint Gradient Balancing for Data Ordering in Finite-Sum Multi-Objective Optimization

Hansi Yang, James Kwok

Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling

Divergence of Neural Tangent Kernel in Classification Problems

Zixiong Yu, Songtao Tian, Guhan Chen

Denoising Levy Probabilistic Models

Dario Shariatian, Umut Simsekli, Alain Oliviero Durmus

Why In-Context Learning Models are Good Few-Shot Learners?

Shiguang Wu, Yaqing Wang, Quanming Yao

Co$^{\mathbf{3}}$Gesture: Towards Coherent Concurrent Co-speech 3D Gesture Generation with Interactive Diffusion

Xingqun Qi, Yatian Wang, Hengyuan Zhang et al.

Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators

Ariel Elnekave, Yair Weiss

The Illustrated AlphaFold

Elana Simon, Jake Silberg

Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation

Anish Abhijit Diwan, Julen Urain, Jens Kober et al.

Improved Convergence Rate for Diffusion Probabilistic Models

Gen Li, Yuchen Jiao

SymDiff: Equivariant Diffusion via Stochastic Symmetrisation

Leo Zhang, Kianoosh Ashouritaklimi, Yee Whye Teh et al.

Prediction Risk and Estimation Risk of the Ridgeless Least Squares Estimator under General Assumptions on Regression Errors

Sungyoon Lee, Sokbae Lee

Efficient Neuron Segmentation in Electron Microscopy by Affinity-Guided Queries

Hang Chen, Chufeng Tang, Xiao Li et al.

Effective post-training embedding compression via temperature control in contrastive training

georgiana dinu, Corey Barrett, Yi Xiang et al.

In vivo cell-type and brain region classification via multimodal contrastive learning

Han Yu, Hanrui Lyu, YiXun Xu et al.

Neural Stochastic Differential Equations for Uncertainty-Aware Offline RL

Cevahir Koprulu, Franck Djeumou, ufuk topcu

Efficient and Robust Neural Combinatorial Optimization via Wasserstein-Based Coresets

Xu Wang, Fuyou Miao, Wenjie Liu et al.

Safety-Prioritizing Curricula for Constrained Reinforcement Learning

Cevahir Koprulu, Thiago Simão, Nils Jansen et al.

Transformers Provably Learn Two-Mixture of Linear Classification via Gradient Flow

Hongru Yang, Zhangyang Wang, Jason Lee et al.

Forewarned is Forearmed: Harnessing LLMs for Data Synthesis via Failure-induced Exploration

Qintong Li, Jiahui Gao, Sheng Wang et al.

CheapNet: Cross-attention on Hierarchical representations for Efficient protein-ligand binding Affinity Prediction

Hyukjun Lim, Sun Kim, Sangseon Lee

Synthesizing Realistic fMRI: A Physiological Dynamics-Driven Hierarchical Diffusion Model for Efficient fMRI Acquisition

Yufan Hu, Jiang, Wuyang Li et al.

How to visualize training dynamics in neural networks

Michael Hu, Shreyans Jain, Sangam Chaulagain et al.

AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data

Tuan Truong, Rithwik Sudharsan, Yibo Yang et al.

Private Mechanism Design via Quantile Estimation

Yuanyuan Yang, Tao Xiao, Bhuvesh Kumar et al.

ST-GCond: Self-supervised and Transferable Graph Dataset Condensation

Beining Yang, Qingyun Sun, Cheng Ji et al.

A new framework for evaluating model out-of-distribution generalisation for the biochemical domain

Raul Fernandez-Diaz, Hoang Thanh Lam, Vanessa Lopez et al.

Straightness of Rectified Flow: A Theoretical Insight into Wasserstein Convergence

Saptarshi Roy, Vansh Bansal, Purnamrita Sarkar et al.

Rare event modeling with self-regularized normalizing flows: what can we learn from a single failure?

Charles Dawson, Van Tran, Max Li et al.

SOREL: A Stochastic Algorithm for Spectral Risks Minimization

Yuze Ge, Rujun Jiang

FairDen: Fair Density-Based Clustering

Lena Krieger, Anna Beer, Pernille Matthews et al.

Learn hybrid prototypes for multivariate time series anomaly detection

Ke-Yuan Shen

Aligned LLMs Are Not Aligned Browser Agents

Priyanshu Kumar, Elaine Lau, Saranya Vijayakumar et al.

Three-in-One: Fast and Accurate Transducer for Hybrid-Autoregressive ASR

Hainan Xu, Travis Bartley, Vladimir Bataev et al.

Sensitivity Verification for Additive Decision Tree Ensembles

Arhaan Ahmad, Tanay Tayal, Ashutosh Gupta et al.

Diffusion Models and Gaussian Flow Matching: Two Sides of the Same Coin

Ruiqi Gao, Emiel Hoogeboom, Jonathan Heek et al.

Sketching for Convex and Nonconvex Regularized Least Squares with Sharp Guarantees

Yingzhen Yang, Ping Li

Problem-Parameter-Free Federated Learning

Wenjing Yan, Kai Zhang, Xiaolu Wang et al.

Finding and Only Finding Differential Nash Equilibria by Both Pretending to be a Follower

Guodong Zhang, Xuchan Bao

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models

Eli Chien, Pan Li, Vamsi Potluru et al.

Fugatto 1: Foundational Generative Audio Transformer Opus 1

Rafael Valle, Rohan Badlani, Zhifeng Kong et al.

Model-Agnostic Knowledge Guided Correction for Improved Neural Surrogate Rollout

Bharat Srikishan, Daniel O'Malley, Mohamed Mehana et al.

Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions

Peiyao Lai, Oren Mangoubi

Leveraging Variable Sparsity to Refine Pareto Stationarity in Multi-Objective Optimization

Zeou Hu, Yaoliang Yu

When do GFlowNets learn the right distribution?

Tiago Silva, Rodrigo Alves, Eliezer de Souza da Silva et al.

Towards a Complete Logical Framework for GNN Expressiveness

Tuo Xu

Rethinking Shapley Value for Negative Interactions in Non-convex Games

Wonjoon Chang, Myeongjin Lee, Jaesik Choi

Matérn Kernels for Tunable Implicit Surface Reconstruction

Maximilian Weiherer, Bernhard Egger

In Search of the Engram in LLMs: A Neuroscience Perspective on the Memory Functions in AI Models

Minsung Kim, Jea Kwon, Dong-Kyum Kim et al.

MAESTRO: Masked Encoding Set Transformer with Self-Distillation

Matthew Lee, Jaesik Kim, Matei Ionita et al.

dEBORA: Efficient Bilevel Optimization-based low-Rank Adaptation

Emanuele Zangrando, Sara Venturini, Francesco Rinaldi et al.

Multi-session, multi-task neural decoding from distinct cell-types and brain regions

Mehdi Azabou, Krystal Pan, Vinam Arora et al.

Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics

Zaige Fei, Fan Xu, Junyuan Mao et al.

CameraCtrl: Enabling Camera Control for Video Diffusion Models

Hao He, Yinghao Xu, Yuwei Guo et al.

Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images

Aiqing Zhu, Yuting Pan, Qianxiao Li

pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation

Shentong Mo, Xufang Luo, Dongsheng Li

ParFam -- (Neural Guided) Symbolic Regression via Continuous Global Optimization

Philipp Scholl, Katharina Bieker, Hillary Hauger et al.

Diff-2-in-1: Bridging Generation and Dense Perception with Diffusion Models

Shuhong Zheng, Zhipeng Bao, Ruoyu Zhao et al.

Exposing and Addressing Cross-Task Inconsistency in Unified Vision-Language Models

Aniruddha Kembhavi, Mohit Bansal, Amita Kamath et al.

Streaming Algorithms For $\ell_p$ Flows and $\ell_p$ Regression

Amit Chakrabarti, Jeffrey Jiang, David Woodruff et al.

Reassessing EMNLP 2024’s Best Paper: Does Divergence-Based Calibration for MIAs Hold Up?

Pratyush Maini, Anshuman Suri

ContraDiff: Planning Towards High Return States via Contrastive Learning

Yixiang Shan, Zhengbang Zhu, Ting Long et al.

Class Distribution-induced Attention Map for Open-vocabulary Semantic Segmentations

Dong Un Kang, Hayeon Kim, Se Young Chun

Reconstruction-Guided Policy: Enhancing Decision-Making through Agent-Wise State Consistency

Qifan Liang, Yixiang Shan, Haipeng Liu et al.

TSVD: Bridging Theory and Practice in Continual Learning with Pre-trained Models

Liangzu Peng, Juan Elenter, Joshua Agterberg et al.

Coreset Spectral Clustering

Ben Jourdan, Gregory Schwartzman, Peter Macgregor et al.

Start Smart: Leveraging Gradients For Enhancing Mask-based XAI Methods

Buelent Uendes, Shujian Yu, Mark Hoogendoorn

Analysing The Spectral Biases in Generative Models

Amitoj Miglani, Shweta Singh, Vidit Aggarwal

Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations

David Dalton, Alan Lazarus, Hao Gao et al.

Bayesian Regularization of Latent Representation

Chukwudi Paul Obite, Zhi Chang, Keyan Wu et al.

DEPfold: RNA Secondary Structure Prediction as Dependency Parsing.

Ke Wang, Shay B Cohen

Open-Source vs Close-Source: The Context Utilization Challenge

Litu Ou

Variational Bayesian Pseudo-Coreset

Hyungi Lee, Seungyoo Lee, Juho Lee

Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML

Ryan McKenna

BoneMet: An Open Large-Scale Multi-Modal Murine Dataset for Breast Cancer Bone Metastasis Diagnosis and Prognosis

Tiankuo Chu, Fudong Lin, Shubo Wang et al.

Size-Generalizable RNA Structure Evaluation by Exploring Hierarchical Geometries

Zongzhao Li, Jiacheng Cen, Wenbing Huang et al.

Semialgebraic Neural Networks: From roots to representations

S David Mis, Matti Lassas, Maarten V de Hoop

ADAPT: Attentive Self-Distillation and Dual-Decoder Prediction Fusion for Continual Panoptic Segmentation

Ze Yang, Shichao Dong, Ruibo Li et al.

Flow With What You Know

Scott Hawley

Difference-of-submodular Bregman Divergence

Masanari Kimura, Takahiro Kawashima, Tasuku Soma et al.

MotherNet: Fast Training and Inference via Hyper-Network Transformers

Andreas Mueller, Carlo Curino, Raghu Ramakrishnan

Provable Convergence Bounds for Hybrid Dynamical Sampling and Optimization

Matthew Burns, Qingyuan Hou, Michael Huang

Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control

Devdhar Patel, Hava Siegelmann

MorphoDiff: Cellular Morphology Painting with Diffusion Models

Zeinab Navidi, Jun Ma, Esteban Miglietta et al.

PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations

Qiang Liu, Huiqiao Fu, Kaiqiang Tang et al.

Rethinking Graph Neural Networks From A Geometric Perspective Of Node Features

Feng Ji, Yanan Zhao, KAI ZHAO et al.

InfoGS: Efficient Structure-Aware 3D Gaussians via Lightweight Information Shaping

Yunchao Zhang, Guandao Yang, Leonidas Guibas et al.

Animate Your Thoughts: Reconstruction of Dynamic Natural Vision from Human Brain Activity

Yizhuo Lu, Changde Du, Chong Wang et al.

Breaking Mental Set to Improve Reasoning through Diverse Multi-Agent Debate

Yexiang Liu, Jie Cao, Zekun Li et al.

Modeling dynamic social vision highlights gaps between deep learning and humans

Kathy Garcia, Emalie McMahon, Colin Conwell et al.

MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling

Rachel Teo, Tan Nguyen

RAG-SR: Retrieval-Augmented Generation for Neural Symbolic Regression

Hengzhe Zhang, Qi Chen, Bing XUE et al.

Joint Reward and Policy Learning with Demonstrations and Human Feedback Improves Alignment

Chenliang Li, Siliang Zeng, Zeyi Liao et al.

SelectFormer in Data Markets: Privacy-Preserving and Efficient Data Selection for Transformers with Multi-Party Computation

Xu Ouyang, Felix Xiaozhu Lin, Yangfeng Ji

Action Sequence Augmentation for Action Anticipation

Yihui Qiu, Deepu Rajan

Near-Exact Privacy Amplification for Matrix Mechanisms

Christopher Choquette-Choo, Arun Ganesh, Saminul Haque et al.

Learning to Select Nodes in Branch and Bound with Sufficient Tree Representation

Sijia Zhang, Shuli Zeng, Shaoang Li et al.

Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning

Dingrong Wang, Krishna Neupane, Ervine Zheng et al.

Accelerating Task Generalisation with Multi-Level Skill Hierarchies

Thomas Cannon, Özgür Şimşek

SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning

Lun Huang, Qiang Qiu, Guillermo Sapiro

DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle

Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen et al.

Balancing Act: Diversity and Consistency in Large Language Model Ensembles

Ahmed Abdulaal, Chen Jin, Nina Montaña-Brown et al.

Curriculum-aware Training for Discriminating Molecular Property Prediction Models

Hansi Yang, Quanming Yao, James Kwok

Rationalizing and Augmenting Dynamic Graph Neural Networks

Guibin Zhang, Yiyan Qi, Ziyang Cheng et al.

Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching

Lile Cai, Chuan Sheng Foo, Xun Xu et al.

A Theoretical Framework for Partially-Observed Reward States in RLHF

Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano et al.

DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance

Liang Sun, Yang Zhang, Weizhao He et al.

MAI: A Multi-turn Aggregation-Iteration Model for Composed Image Retrieval

Yanzhe Chen, Zhiwen Yang, Jinglin Xu et al.

kNN Attention Demystified: A Theoretical Exploration for Scalable Transformers

Themistoklis Haris

Towards Unified Human Motion-Language Understanding via Sparse Interpretable Characterization

guangtao lyu, Chenghao Xu, Jiexi Yan et al.

Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training

Boyu Liu, Haoyu Huang, Linlin Yang et al.

Regularizing Energy among Training Samples for Out-of-Distribution Generalization

Yiting Chen, Qitian Wu, Junchi Yan

Rethinking and Improving Autoformalization: Towards a Faithful Metric and a Dependency Retrieval-based Approach

Qi Liu, Xinhao Zheng, Xudong Lu et al.

Learning Structured Universe Graph with Outlier OOD Detection for Partial Matching

Zetian Jiang, Jiaxin Lu, Haizhao Fan et al.

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

Wenzheng Pan, Hao Xiong, Jiale Ma et al.

Learning Geometric Reasoning Networks For Robot Task And Motion Planning

Smail Ait Bouhsain, Rachid Alami, Thierry Simeon

Fine-Tuning Token-Based Large Multimodal Models: What Works, What Doesn’t and What's Next

Zhulin Hu, Yan Ma, Jiadi Su et al.