Most Cited 2025 "object-proposal association" Papers

Local Loss Optimization in the Infinite Width: Stable Parameterization of Predictive Coding Networks and Target Propagation

Satoki Ishikawa, Rio Yokota, Ryo Karakida

Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling

Yuxuan YAO, Han Wu, Mingyang LIU et al.

State Space Model Meets Transformer: A New Paradigm for 3D Object Detection

Chuxin Wang, Wenfei Yang, Xiang Liu et al.

A primer on analytical learning dynamics of nonlinear neural networks

Rodrigo Carrasco-Davis, Erin Grant

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting

Yong Liu, Guo Qin, Xiangdong Huang et al.

Neural Fluid Simulation on Geometric Surfaces

Haoxiang Wang, Tao Yu, Hui Qiao et al.

PWM: Policy Learning with Multi-Task World Models

Ignat Georgiev, Varun Giridhar, Nick Hansen et al.

Adaptive $Q$-Network: On-the-fly Target Selection for Deep Reinforcement Learning

Théo Vincent, Fabian Wahren, Jan Peters et al.

Do Contemporary Causal Inference Models Capture Real-World Heterogeneity? Findings from a Large-Scale Benchmark

Haining Yu, Yizhou Sun

Point-based Instance Completion with Scene Constraints

Wesley Khademi, Li Fuxin

Spectral Compressive Imaging via Unmixing-driven Subspace Diffusion Refinement

Haijin Zeng, Benteng Sun, Yongyong Chen et al.

Unifying Causal Representation Learning with the Invariance Principle

Dingling Yao, Dario Rancati, Riccardo Cadei et al.

Deep Signature: Characterization of Large-Scale Molecular Dynamics

Tiexin Qin, Mengxu ZHU, Chunyang Li et al.

InstaSHAP: Interpretable Additive Models Explain Shapley Values Instantly

James Enouen, Yan Liu

LLMs' Potential Influences on Our Democracy: Challenges and Opportunities

Yujin Potter, David Rand, Yejin Choi et al.

Solving hidden monotone variational inequalities with surrogate losses

Ryan D'Orazio, Danilo Vucetic, Zichu Liu et al.

Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos

Dayal Singh Kalra, Tianyu He, Maissam Barkeshli

Dynamic Low-Rank Sparse Adaptation for Large Language Models

Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.

Identifiability for Gaussian Processes with Holomorphic Kernels

Ameer Qaqish, Didong Li

Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation

Chendi Ge, Xin Wang, Ziwei Zhang et al.

DABL: Detecting Semantic Anomalies in Business Processes Using Large Language Models

Wei Guan, Jian Cao, Jianqi Gao et al.

Is Your Video Language Model a Reliable Judge?

Ming Liu, Wensheng Zhang

Param$\Delta$ for Direct Mixing: Post-Train Large Language Model At Zero Cost

Sheng Cao, Mingrui Wu, Karthik Prasad et al.

Dualformer: Controllable Fast and Slow Thinking by Learning with Randomized Reasoning Traces

Andy (DiJia) Su, Sainbayar Sukhbaatar, Michael Rabbat et al.

CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair

Mingjie Liu, Yun-Da Tsai, Wenfei Zhou et al.

Latent Bayesian Optimization via Autoregressive Normalizing Flows

Seunghun Lee, Jinyoung Park, Jaewon Chu et al.

Tuning Frequency Bias of State Space Models

Annan Yu, Dongwei Lyu, Soon Hoe Lim et al.

Interpreting the Second-Order Effects of Neurons in CLIP

Yossi Gandelsman, Alexei Efros, Jacob Steinhardt

Interpreting and Editing Vision-Language Representations to Mitigate Hallucinations

Nick Jiang, Anish Kachinthaya, Suzanne Petryk et al.

Model-agnostic meta-learners for estimating heterogeneous treatment effects over time

Dennis Frauen, Konstantin Hess, Stefan Feuerriegel

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning

Amrith Setlur, Chirag Nagpal, Adam Fisch et al.

Zero-shot Model-based Reinforcement Learning using Large Language Models

Abdelhakim Benechehab, Youssef Attia El Hili, Ambroise Odonnat et al.

Sufficient Context: A New Lens on Retrieval Augmented Generation Systems

Hailey Joren, Jianyi Zhang, Chun-Sung Ferng et al.

A Large-Scale 3D Face Mesh Video Dataset via Neural Re-parameterized Optimization

Kim Youwang, Lee Hyun, Kim Sung-Bin et al.

Semantic Aware Representation Learning for Lifelong Learning

Fahad Sarfraz, Elahe Arani, Bahram Zonooz

Detecting Backdoor Samples in Contrastive Language Image Pretraining

Hanxun Huang, Sarah Erfani, Yige Li et al.

The Value of Sensory Information to a Robot

Arjun Krishna, Edward Hu, Dinesh Jayaraman

metabench - A Sparse Benchmark of Reasoning and Knowledge in Large Language Models

Alex Kipnis, Konstantinos Voudouris, Luca Schulze Buschoff et al.

Revolutionizing EMCCD Denoising through a Novel Physics-Based Learning Framework for Noise Modeling

Haiyang Jiang, Tetsuichi Wazawa, Imari Sato et al.

Memory Efficient Transformer Adapter for Dense Predictions

Dong Zhang, Rui Yan, Pingcheng Dong et al.

DiffPuter: Empowering Diffusion Models for Missing Data Imputation

Hengrui Zhang, Liancheng Fang, Qitian Wu et al.

Generating Likely Counterfactuals Using Sum-Product Networks

Jiří Němeček, Tomáš Pevný, Jakub Marecek

The Foundations of Tokenization: Statistical and Computational Concerns

Juan Luis Gastaldi, John Terilla, Luca Malagutti et al.

A General Framework for Off-Policy Learning with Partially-Observed Reward

Rikiya Takehi, Masahiro Asami, Kosuke Kawakami et al.

Rethinking Graph Prompts: Unraveling the Power of Data Manipulation in Graph Neural Networks

Chenyi Zi, Bowen LIU, Xiangguo SUN et al.

Joint Fine-tuning and Conversion of Pretrained Speech and Language Models towards Linear Complexity

Mutian He, Philip N. Garner

Neural Wave Equation for Irregularly Sampled Sequence Data

Arkaprava Majumdar, M Anand Krishna, P. K. Srijith

Understanding Long Videos with Multimodal Language Models

Kanchana Ranasinghe, Xiang Li, Kumara Kahatapitiya et al.

Protecting against simultaneous data poisoning attacks

Neel Alex, Muhammad Shoaib Ahmed Siddiqui, Amartya Sanyal et al.

Rethinking Reward Modeling in Preference-based Large Language Model Alignment

Hao Sun, Yunyi Shen, Jean-Francois Ton

X-ALMA: Plug & Play Modules and Adaptive Rejection for Quality Translation at Scale

Haoran Xu, Kenton Murray, Philipp Koehn et al.

Semantix: An Energy-guided Sampler for Semantic Style Transfer

Huiang He, Minghui HU, Chuanxia Zheng et al.

Efficient Off-Policy Learning for High-Dimensional Action Spaces

Fabian Otto, Philipp Becker, Vien A Ngo et al.

RandLoRA: Full rank parameter-efficient fine-tuning of large models

Paul Albert, Frederic Zhang, Hemanth Saratchandran et al.

Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs

Yuhan Chen, Yihong Luo, Yifan Song et al.

Optimal Protocols for Continual Learning via Statistical Physics and Control Theory

Francesco Mori, Stefano Sarao Mannelli, Francesca Mignacco

Unveiling the Knowledge of CLIP for Training-Free Open-Vocabulary Semantic Segmentation

Yajie Liu, Guodong Wang, Jinjin Zhang et al.

CONGO: Compressive Online Gradient Optimization

Jeremy Carleton, Prathik Vijaykumar, Divyanshu Saxena et al.

ToVE: Efficient Vision-Language Learning via Knowledge Transfer from Vision Experts

Yuanchen Wu, Junlong Du, Ke Yan et al.

Edge-aware Image Smoothing with Relative Wavelet Domain Representation

Huiqing Qi, Xiaoliu Luo, Tingting Li et al.

When does compositional structure yield compositional generalization? A kernel theory.

Samuel Lippl, Kimberly Stachenfeld

TVNet: A Novel Time Series Analysis Method Based on Dynamic Convolution and 3D-Variation

Chenghan Li, Mingchen LI, Ruisheng Diao

Provable unlearning in topic modeling and downstream tasks

Stanley Wei, Sadhika Malladi, Sanjeev Arora et al.

Object-Centric Pretraining via Target Encoder Bootstrapping

Nikola Đukić, Tim Lebailly, Tinne Tuytelaars

LASeR: Towards Diversified and Generalizable Robot Design with Large Language Models

JUNRU SONG, Yang Yang, Huan Xiao et al.

Bridging Traffic State and Trajectory for Dynamic Road Network and Trajectory Representation Learning

Chengkai Han, Jingyuan Wang, Yongyao Wang et al.

Unaligned Message-Passing and Contextualized-Pretraining for Robust Geo-Entity Resolution

Yuwen Ji, Wenbo Xie, Jiaqi Zhang et al.

PiCO: Peer Review in LLMs based on Consistency Optimization

Kun-Peng Ning, Shuo Yang, Yuyang Liu et al.

Can We Ignore Labels in Out of Distribution Detection?

Hong Yang, Qi Yu, Travis Desell

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

Xiangyu Dong, Xingyi Zhang, Lei Chen et al.

ADePT: Adaptive Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning

Pengwei Tang, Xiaolin Hu, Yong Liu

Fast Direct: Query-Efficient Online Black-box Guidance for Diffusion-model Target Generation

Kim Yong Tan, YUEMING LYU, Ivor Tsang et al.

Competitive Fair Scheduling with Predictions

Tianming Zhao, Chunqiu xia, Xiaomin Chang et al.

Online-to-Offline RL for Agent Alignment

Xu Liu, Haobo Fu, Stefano V. Albrecht et al.

On the Benefits of Memory for Modeling Time-Dependent PDEs

Ricardo Buitrago Ruiz, Tanya Marwah, Albert Gu et al.

The Case for Cleaner Biosignals: High-fidelity Neural Compressor Enables Transfer from Cleaner iEEG to Noisier EEG

Francesco Carzaniga, Gary Hoppeler, Michael Hersche et al.

Do LLMs have Consistent Values?

Naama Rozen, Liat Bezalel, Gal Elidan et al.

Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional, Black-box Systems

Dan MacKinlay, Russell Tsuchida, Daniel Pagendam et al.

Adaptive Transformer Programs: Bridging the Gap Between Performance and Interpretability in Transformers

Quoc-Vinh Lai-Dang, Taemin Kang, Seungah Son

A Causal Lens for Learning Long-term Fair Policies

Jacob Lear, Lu Zhang

ComaDICE: Offline Cooperative Multi-Agent Reinforcement Learning with Stationary Distribution Shift Regularization

The Viet Bui, Thanh Nguyen, Tien Mai

ControlAR: Controllable Image Generation with Autoregressive Models

Zongming Li, Tianheng Cheng, Shoufa Chen et al.

Fat-to-Thin Policy Optimization: Offline Reinforcement Learning with Sparse Policies

Lingwei Zhu, Han Wang, Yukie Nagai

Mind the Gap: Examining the Self-Improvement Capabilities of Large Language Models

Yuda Song, Hanlin Zhang, Carson Eisenach et al.

RetroInText: A Multimodal Large Language Model Enhanced Framework for Retrosynthetic Planning via In-Context Representation Learning

Chenglong Kang, Xiaoyi Liu, Fei Guo

PhyloLM: Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks

Nicolas Yax, Pierre-Yves Oudeyer, Stefano Palminteri

Improving Text-to-Image Consistency via Automatic Prompt Optimization

Melissa Hall, Michal Drozdzal, Oscar Mañas et al.

OvercookedV2: Rethinking Overcooked for Zero-Shot Coordination

Tobias Gessler, Tin Dizdarevic, Ani Calinescu et al.

Score-based free-form architectures for high-dimensional Fokker-Planck equations

Feng Liu, Faguo Wu, Xiao Zhang

ACTIVE: Offline Reinforcement Learning via Adaptive Imitation and In-sample $V$-Ensemble

Tianyuan Chen, Ronglong Cai, Faguo Wu et al.

Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence

Dharmesh Tailor, Alvaro Correia, Eric Nalisnick et al.

Reveal Object in Lensless Photography via Region Gaze and Amplification

Xiangjun Yin, Huihui Yue

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.

See Through Their Minds: Learning Transferable Brain Decoding Models from Cross-Subject fMRI

Yulong Liu, Yongqiang Ma, Guibo Zhu et al.

Open-Set Graph Anomaly Detection via Normal Structure Regularisation

Qizhou Wang, Guansong Pang, Mahsa Salehi et al.

Balancing Bias in Two-sided Markets for Fair Stable Matchings

Siyuan Wu, Leong Hou U, Panagiotis Karras

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.

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.

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.

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.

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.

Minimalistic Predictions for Online Class Constraint Scheduling

Dorian Guyot, Alexandra Lassota

Shifting the Paradigm: A Diffeomorphism Between Time Series Data Manifolds for Achieving Shift-Invariancy in Deep Learning

Berken Utku Demirel, Christian Holz

Simulating Training Dynamics to Reconstruct Training Data from Deep Neural Networks

Hanling Tian, Yuhang Liu, Mingzhen He 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.

Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective

Andrew Jesson, Nicolas Beltran-Velez, David Blei

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.

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.

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.

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

Lvmin Zhang, Anyi Rao, Maneesh Agrawala

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.

Training Verification-Friendly Neural Networks via Neuron Behavior Consistency

Zongxin Liu, Zhe Zhao, Fu Song 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

Explore Theory of Mind: program-guided adversarial data generation for theory of mind reasoning

Melanie Sclar, Jane Dwivedi-Yu, Maryam Fazel-Zarandi et al.

Linear Recurrences Accessible to Everyone

Felix Sarnthein

Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations

Julius Aka, Johannes Brunnemann, Jörg Eiden 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

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.

Gap Preserving Distillation by Building Bidirectional Mappings with A Dynamic Teacher

Yong Guo, Shulian Zhang, Haolin Pan 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.

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

Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval

Pengcheng Jiang, Cao (Danica) Xiao, Minhao Jiang et al.

TabReD: Analyzing Pitfalls and Filling the Gaps in Tabular Deep Learning Benchmarks

Ivan Rubachev, Nikolay Kartashev, Yury Gorishniy et al.

Learning to Discover Regulatory Elements for Gene Expression Prediction

Xingyu Su, Haiyang Yu, Degui Zhi et al.

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

Woosung Koh, Wonbeen Oh, Siyeol Kim et al.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics

Keyi Shen, Jiangwei Yu, Jose Barreiros et al.

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.

Demystifying the Token Dynamics of Deep Selective State Space Models

Thieu Vo, Duy-Tung Pham, Xin Tong et al.

Iterative Label Refinement Matters More than Preference Optimization under Weak Supervision

Yaowen Ye, Cassidy Laidlaw, Jacob Steinhardt

MixMax: Distributional Robustness in Function Space via Optimal Data Mixtures

Anvith Thudi, Chris Maddison

Improving Unsupervised Constituency Parsing via Maximizing Semantic Information

Junjie Chen, Xiangheng He, Yusuke Miyao 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.

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.

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

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.

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.

Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Fangyu Lei, Jixuan Chen, Yuxiao Ye 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

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

Towards Neural Scaling Laws for Time Series Foundation Models

Qingren Yao, Chao-Han Huck Yang, Renhe Jiang et al.

On the Modeling Capabilities of Large Language Models for Sequential Decision Making

Martin Klissarov, R Devon Hjelm, Alexander Toshev et al.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency

Qixin ZHANG, Zongqi Wan, Yu Yang 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

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.

Sharpness-Aware Black-Box Optimization

Feiyang YE, YUEMING LYU, Xuehao Wang et al.

Better Instruction-Following Through Minimum Bayes Risk

Ian Wu, Patrick Fernandes, Amanda Bertsch et al.

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

Hansi Yang, James Kwok

Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs

Yu-Zhe Shi, Mingchen Liu, Fanxu Meng et al.

Manifold Constraint Reduces Exposure Bias in Accelerated Diffusion Sampling

Learning Multi-Index Models with Neural Networks via Mean-Field Langevin Dynamics

Alireza Mousavi-Hosseini, Denny Wu, Murat A Erdogdu

Sensitivity-Aware Amortized Bayesian Inference

Lasse Elsemüller, Hans Olischläger, Marvin Schmitt et al.

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.