yusuke1997/dblp-id-title huggingface dataset:
More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory
Long Context Compression with Activation Beacon
Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
Steerable Partial Differential Operators for Equivariant Neural Networks
Protein Representation Learning via Knowledge Enhanced Primary Structure Reasoning
CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
Learning to Guide and to be Guided in the Architect-Builder Problem
AMRL: Aggregated Memory For Reinforcement Learning
Learning-based Support Estimation in Sublinear Time
Stochastic Variational Video Prediction
Iterative energy-based projection on a normal data manifold for anomaly localization
Adaptive Shrinkage Estimation for Personalized Deep Kernel Regression in Modeling Brain Trajectories
Phase-Aware Speech Enhancement with Deep Complex U-Net
BlockSwap: Fisher-guided Block Substitution for Network Compression on a Budget
Federated Learning on Small Batch Sizes via Batch Renormalization
On the benefits of maximum likelihood estimation for Regression and Forecasting
Linear Transformer Topological Masking with Graph Random Features
Only Pay for What Is Uncertain: Variance-Adaptive Thompson Sampling
Unsupervised Clustering using Pseudo-semi-supervised Learning
Shape-Texture Debiased Neural Network Training
Descent with Misaligned Gradients and Applications to Hidden Convexity
Multiplicative Interactions and Where to Find Them
Pushing the Limits of Fewshot Anomaly Detection in Industry Vision: Graphcore
Speaker-Invariant Speech Recognition through Fine-Tuning on Individual-Specific Data with Voice Conversion
DAFA: Distance-Aware Fair Adversarial Training
Towards Generative Abstract Reasoning: Completing Raven's Progressive Matrix via Rule Abstraction and Selection
NeSyC: A Neuro-symbolic Continual Learner For Complex Embodied Tasks in Open Domains
Counting Graph Substructures with Graph Neural Networks
Physics-aligned field reconstruction with diffusion bridge
Evading Adversarial Example Detection Defenses with Orthogonal Projected Gradient Descent
Learning N: M Fine-grained Structured Sparse Neural Networks From Scratch
PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidance
Differentiable Segmentation of Sequences
FedP3: Federated Personalized and Privacy-friendly Network Pruning under Model Heterogeneity
Masked Unsupervised Self-training for Label-free Image Classification
Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization
UniFormer: Unified Transformer for Efficient Spatial-Temporal Representation Learning
SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
KL Guided Domain Adaptation
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s)
Uni-Match: A Semantic Unified Model for Query-Product Retrieval
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
Identifying latent state transitions in non-linear dynamical systems
CktGNN: Circuit Graph Neural Network for Electronic Design Automation
On the Joint Interaction of Models, Data, and Features
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
Can BERT Refrain from Forgetting on Sequential Tasks? A Probing Study
Decoupled Marked Temporal Point Process using Neural Ordinary Differential Equations
Dreamweaver: Learning Compositional World Models from Pixels
Disentangled State Space Models: Unsupervised Learning of dynamics across Heterogeneous Environments
Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning
Reward Learning from Multiple Feedback Types
Online variance-reducing optimization
Can Arterial Blood Pressure Predict Age? A ConvNet Classification Task
Revisiting Locally Supervised Learning: an Alternative to End-to-end Training
Rethinking Architecture Selection in Differentiable NAS
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks
You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction
Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
Dynamic Loss-Based Sample Reweighting for Improved Large Language Model Pretraining
Differentiable learning of numerical rules in knowledge graphs
Optimal Strategies Against Generative Attacks
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Accelerated Policy Learning with Parallel Differentiable Simulation
ClimODE: Climate and Weather Forecasting with Physics-informed Neural ODEs
AGRO: Adversarial discovery of error-prone Groups for Robust Optimization
Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents
Prototype memory and attention mechanisms for few shot image generation
Learning to Compose Words into Sentences with Reinforcement Learning
Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction
cGANs with Projection Discriminator
Understanding In-Context Learning from Repetitions
How Does Vision-Language Adaptation Impact the Safety of Vision Language Models?
ConMix: Contrastive Mixup at Representation Level for Long-tailed Deep Clustering
On the duality between contrastive and non-contrastive self-supervised learning
A Multiscale Frequency Domain Causal Framework for Enhanced Pathological Analysis
Scaling Symbolic Methods using Gradients for Neural Model Explanation
DARTS: Differentiable Architecture Search
Unlearning-based Neural Interpretations
Learning Multi-Agent Communication from Graph Modeling Perspective
UMEC: Unified model and embedding compression for efficient recommendation systems
Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together!
Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
A Lie Group Approach to Riemannian Batch Normalization
Data Efficient Language-Supervised Zero-Shot Recognition with Optimal Transport Distillation
Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models
Explicit Box Detection Unifies End-to-End Multi-Person Pose Estimation
A Variational Condition for Minimal-Residual Latent Representations
Gradient Projection Memory for Continual Learning
Hot-Refresh Model Upgrades with Regression-Free Compatible Training in Image Retrieval
BroGNet: Momentum-Conserving Graph Neural Stochastic Differential Equation for Learning Brownian Dynamics
Async-RED: A Provably Convergent Asynchronous Block Parallel Stochastic Method using Deep Denoising Priors
Statistically Optimal K-means Clustering via Nonnegative Low-rank Semidefinite Programming
Learning Disentangled Representations with Wasserstein Auto-Encoders
Guiding Energy-based Models via Contrastive Latent Variables
Conformal Prediction via Regression-as-Classification
Generalized Energy Based Models
Balancing performance and complexity with adaptive graph coarsening
Ring-A-Bell! How Reliable are Concept Removal Methods For Diffusion Models?
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations
ND-SDF: Learning Normal Deflection Fields for High-Fidelity Indoor Reconstruction
Spectro-Riemannian Graph Neural Networks
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Reasoning Elicitation in Language Models via Counterfactual Feedback
Can One Modality Model Synergize Training of Other Modality Models?
JudgeLM: Fine-tuned Large Language Models are Scalable Judges
Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework
Vertical Federated Learning with Missing Features During Training and Inference
PhyloGFN: Phylogenetic inference with generative flow networks
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
BrainUICL: An Unsupervised Individual Continual Learning Framework for EEG Applications
Return-Based Contrastive Representation Learning for Reinforcement Learning
Half-Inverse Gradients for Physical Deep Learning
Restricting the Flow: Information Bottlenecks for Attribution
Towards Better Selective Classification
Advantage Alignment Algorithms
Deep 3D Pan via local adaptive "t-shaped" convolutions with global and local adaptive dilations
Eia: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
CNN Kernels Can Be the Best Shapelets
Evolutionary Diversity Optimization with Clustering-based Selection for Reinforcement Learning
Robust Training of Federated Models with Extremely Label Deficiency
LICO: Large Language Models for In-Context Molecular Optimization
The Three Stages of Learning Dynamics in High-dimensional Kernel Methods
Fast Node Embeddings: Learning Ego-Centric Representations
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
On Harmonizing Implicit Subpopulations
Model-Augmented Actor-Critic: Backpropagating through Paths
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
Pre-training Text-to-Text Transformers for Concept-centric Common Sense
Kernelized Wasserstein Natural Gradient
How Low Can You Go? Searching for the Intrinsic Dimensionality of Complex Networks using Metric Node Embeddings
One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks
Attribute-based Visual Reprogramming for Vision-Language Models
Adaptive Q-Network: On-the-fly Target Selection for Deep Reinforcement Learning
Sparse Mixture-of-Experts are Domain Generalizable Learners
EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models
Capturing the Temporal Dependence of Training Data Influence
AnomalyCLIP: Object-agnostic Prompt Learning for Zero-shot Anomaly Detection
Learning with a Mole: Transferable latent spatial representations for navigation without reconstruction
Teaching with Commentaries
Exploring Deep Recurrent Models with Reinforcement Learning for Molecule Design
Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks
Representing Formal Languages: A Comparison Between Finite Automata and Recurrent Neural Networks
In-Situ Text-Only Adaptation of Speech Models with Low-Overhead Speech Imputations
Song From PI: A Musically Plausible Network for Pop Music Generation
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality
Ctrl-Adapter: An Efficient and Versatile Framework for Adapting Diverse Controls to Any Diffusion Model
Deep Convolutional Networks as shallow Gaussian Processes
Learning to Remember More with Less Memorization
Fast Chirplet Transform Injects Priors in Deep Learning of Animal Calls and Speech
Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations
Distilling Model Failures as Directions in Latent Space
Orthogonalizing Convolutional Layers with the Cayley Transform
Perm: A Parametric Representation for Multi-Style 3D Hair Modeling
DiffPuter: Empowering Diffusion Models for Missing Data Imputation
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
Simplifying Deep Temporal Difference Learning
Kernel Change-point Detection with Auxiliary Deep Generative Models
A Plug-and-Play Image Registration Network
Fixed-Budget Differentially Private Best Arm Identification
Field-DiT: Diffusion Transformer on Unified Video, 3D, and Game Field Generation
Topological Experience Replay
Meta-Learning Probabilistic Inference for Prediction
Rethinking Complex Queries on Knowledge Graphs with Neural Link Predictors
When Selection Meets Intervention: Additional Complexities in Causal Discovery
On the Convergence of mSGD and AdaGrad for Stochastic Optimization
Spike-based causal inference for weight alignment
Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback
$\mathrm{SO}(2)$-Equivariant Reinforcement Learning
Memory Augmented Control Networks
Towards Explaining the Power of Constant-depth Graph Neural Networks for Structured Linear Programming
Str2Str: A Score-based Framework for Zero-shot Protein Conformation Sampling
Why Propagate Alone? Parallel Use of Labels and Features on Graphs
Learning the Pareto Front with Hypernetworks
UniCoTT: A Unified Framework for Structural Chain-of-Thought Distillation
Harnessing Density Ratios for Online Reinforcement Learning
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification
Porf: Pose residual field for accurate Neural surface Reconstruction
Adversarial Search Engine Optimization for Large Language Models
Generalized Schrödinger Bridge Matching
Data Noising as Smoothing in Neural Network Language Models
Learning Approximate Inference Networks for Structured Prediction
SAM as an Optimal Relaxation of Bayes
SDSRA: A Skill-Driven Skill-Recombination Algorithm for Efficient Policy Learning
ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret
BTBS-LNS: Binarized-Tightening, Branch and Search on Learning LNS Policies for MIP
ECHOPulse: ECG Controlled Echocardio-gram Video Generation
Efficient Modulation for Vision Networks
Conservative Uncertainty Estimation By Fitting Prior Networks
Transformer Embeddings of Irregularly Spaced Events and Their Participants
Unsupervised Discovery of 3D Physical Objects from Video
Grokking in Linear Estimators - A Solvable Model that Groks without Understanding
Consistent Counterfactuals for Deep Models
Do Large Language Models Truly Understand Geometric Structures?
A Probabilistic Perspective on Unlearning and Alignment for Large Language Models
Functional Interpolation for Relative Positions improves Long Context Transformers
Sort-free Gaussian Splatting via Weighted Sum Rendering
DexDeform: Dexterous Deformable Object Manipulation with Human Demonstrations and Differentiable Physics
Synthio: Augmenting Small-Scale Audio Classification Datasets with Synthetic Data
User-Interactive Offline Reinforcement Learning
VL-BERT: Pre-training of Generic Visual-Linguistic Representations
Does enhanced shape bias improve neural network robustness to common corruptions?
Reward-Free Curricula for Training Robust World Models
LLMCarbon: Modeling the End-to-End Carbon Footprint of Large Language Models
Unified Visual Transformer Compression
Graph Neural Networks with Learnable Structural and Positional Representations
Regularizing activations in neural networks via distribution matching with the Wasserstein metric
Unsupervised Meta-learning via Few-shot Pseudo-supervised Contrastive Learning
Looped Transformers for Length Generalization
Recursive Disentanglement Network
Leveraging Unlabeled Data to Track Memorization
On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length
Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks
Overlearning Reveals Sensitive Attributes
TPO: Aligning Large Language Models with Multi-branch & Multi-step Preference Trees
Deep Networks Learn Features From Local Discontinuities in the Label Function
REBAR: Retrieval-Based Reconstruction for Time-series Contrastive Learning
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
Earlier Tokens Contribute More: Learning Direct Preference Optimization From Temporal Decay Perspective
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
Measuring And Improving Persuasiveness Of Large Language Models
A Precise Characterization of SGD Stability Using Loss Surface Geometry
Deep Kernel Relative Test for Machine-generated Text Detection
Safe Neurosymbolic Learning with Differentiable Symbolic Execution
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Faster Approximation of Probabilistic and Distributional Values via Least Squares
Provable weak-to-strong generalization via benign overfitting
ILLUSION: Unveiling Truth with a Comprehensive Multi-Modal, Multi-Lingual Deepfake Dataset
Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
Variational Continual Learning
Regret Bounds for Episodic Risk-Sensitive Linear Quadratic Regulator
Post-hoc bias scoring is optimal for fair classification
The Limitations of Adversarial Training and the Blind-Spot Attack
Training Triplet Networks with GAN
Certified Robustness for Deep Equilibrium Models via Interval Bound Propagation
Generating Freeform Endoskeletal Robots
Reward Constrained Policy Optimization
Audio vs. Text: Identify a Powerful Modality for Effective Hate Speech Detection
HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Minimizing FLOPs to Learn Efficient Sparse Representations
A differentiable BLEU loss. Analysis and first results
LMSeg: Language-guided Multi-dataset Segmentation
Distributionally Robust Federated Learning with Wasserstein Barycenter
Unlocking the Power of Representations in Long-term Novelty-based Exploration
CG-Bench: Clue-grounded Question Answering Benchmark for Long Video Understanding
What Makes Instance Discrimination Good for Transfer Learning?
Unsupervised Learning for Combinatorial Optimization Needs Meta Learning
When, Why, and Which Pretrained GANs Are Useful?
Leveraging Good Intentions to Reduce Malicious Network Traffic
Using Routing and Tunneling to Combat DoS Attacks
Efficient and Secure Source Authentication with Packet Passports
HoneySpam: Honeypots Fighting Spam at the Source
Push vs. Pull: Implications of Protocol Design on Controlling Unwanted Traffic
An Architecture for Developing Behavioral History
Analyzing Cooperative Containment of Fast Scanning Worms
A New Service for Increasing the Effectiveness of Network Address Blacklists
Lightweight Encryption for Email
Reducing Unwanted Traffic in a Backbone Network
Boundary Detection and Containment of Local Worm Infections
The Rising Tide: DDoS from Defective Designs and Defaults
Cookies Along Trust-Boundaries (CAT): Accurate and Deployable Flood Protection
Tracking the Role of Adversaries in Measuring Unwanted Traffic
Steps to Reducing Unwanted Traffic on the Internet Workshop, SRUTI'05, Cambridge, MA, USA, July 7, 2005
Adaptive Defense Against Various Network Attacks
3rd Workshop on Steps to Reducing Unwanted Traffic on the Internet, SRUTI'07, Santa Clara, CA, USA, June 18, 2007
Analyzing Network and Content Characteristics of Spim Using Honeypots
The Zombie Roundup: Understanding, Detecting, and Disrupting Botnets
Detecting Spam in VoIP Networks
2nd Workshop on Steps to Reducing Unwanted Traffic on the Internet, SRUTI'06, San Jose, CA, USA, July 7, 2006
Strider Typo-Patrol: Discovery and Analysis of Systematic Typo-Squatting
Stress Testing Traffic to Infer Its Legitimacy
The Spoofer Project: Inferring the Extent of Internet Source Address Filtering on the Internet
BotTorrent: Misusing BitTorrent to Launch DDoS Attacks
Improving Spam Detection Based on Structural Similarity
Revealing Botnet Membership Using DNSBL Counter-Intelligence
An Algorithm for Anomaly-based Botnet Detection
Separating Wheat from the Chaff: A Deployable Approach to Counter Spam
Virtual Reality and Cognitive Processes
Bergson's Virtual Action
Virtual Reality: Reflections of Chances, Changes and Dangers in Communicating Knowledge with the Help of VR-Technologies
Psychological Perspective on Virtual Reality
A Framework for Optimising Network Usage for Plausible Distributed Virtual Environments
Rethinking Boundaries
The Grammar of relative Adjectives and Comparison
Semantic Memory Retrieval: Some Data and a Model
Models of Speech Production
Virtual Science: Virutality and Knowledge Acquisition in Science and Cognition
(Re)constructing (Virtual) Reality
Virtual Reality in Surgery: Between Satisfaction and Stress
Theories of the Brain; Behavior, the Mind, Robots and Cognitive Processes, Respectively
Implication as an Alternative to Set-Inclusion as the Semantic Primitive
Two Classes of Holographic Processes Realizable in the Neutral Realm
On the Notion of a Rule
From Reality to the "the Real": Using Augmented Virtual Reality for Training
Virtual Reality: Cognitive Foundations, Technological Issues & Philosophical Implications
VR and Web Page Support in Civil Engineering Education
A Simple Hierarchical Model of Natural Selection
Formal Aspects of Cognitive Processes, Interdisciplinary Conference, Ann Arbor, MI, USA, March 1972
Exploring the Concept of Virtuality: Technological Approaches and Implications from Tele-Education
Empirical Restrictions on the Power of Transformation Grammars
Predicate Calculus Feature Generation
Virtuality and Plurality
Virtual Reality, Cyberspace and Living Organisms: Towards a New Understanding of Perception and Cognition?
The Emotional Talking Virutal Humans
Madness & Virtuality: An Approximation
Computed Navigation in Cranio-Maxillo-Facial and Oral Head and Neck Surgery: Principles, Indications and Potentials for Telepresence and Teleassistance
Towards a Theory of Linguistic Memory
A Mathematical Model for Perception Applied to the Perception of Pitch
Structured-Storage AFA (Abstract)
Poster: Programming Rules by Demonstration in Virtual Reality
Designing Adaptive User Interfaces for People with Dementia: Findings from Participatory Research
Keep it simple: reward and task design in crowdsourcing
Designing Human-Centric Foundation Models
Profile-Based Algorithm for Personalized Gamification in Computer-Supported Collaborative Learning Environments
GenAI for Debiasing: Evaluating a Custom Chatbot as Reflective Partner in Sustainable Design Education
A Framework to Support Multiple Levels of Interaction
1st Workshop on Data Craft as Boundary AI Practice
The influence of user personality and rating scale features on rating behaviour: an empirical study
GHItaly 2017: Game-Computer Interaction in Research
Using hands as an easy UAV joystick for entertainment applications
Advanced Visual Interfaces Supporting Distributed Cloud-Based Big Data Analysis
Emerging informal learning 2.0 practices: a preliminary exploration
Interacting with augmented paper maps: a user experience study
Modeling and Simulating Empathic Behavior in Social Assistive Robots
Gamification for crowdsourced data collection in mobile usability field studies
Prioritizing Usability in Programming Environments for Children
Style Matters: Exploring the Role of Art Style in AI-Generated Images on Engagement in a Gamified Text Labelling Interface
Thinking with the body: a case study from choreography
Instagram Reactions to a Virtual Dining Companion: Qualitative Coding vs. Automated Sentiment Analysis
Designing the internet of tangible things for outdoors environments with university students
Towards persuasive sociometric technologies for inclusive educational settings
HoloLens-based Mixed Reality Experiences for Subjects with Alzheimer's Disease
Authoring tool for Data Journalists integrating Self-Explanatory Visualization Onboarding Concept for a Treemap Visualization
Designing Human-Centered Code Completion Tools in the Age of Generative AI
MCI Older Adults' User Experience with Introverted and Extraverted Humanoid Robot Personalities
The Use of Interactive Technologies for Education in Pandemic and Post-Pandemic Contexts: Design Implications
A Link Back to MemoryLane: The Role of Context in Bookmarking and Refinding
A Design Space for Exploring Rich and Complex Information Environments
'Thinking Problematically' as a Resource for AI Design in Politicised Contexts
Evaluating LLMs for Synthetic Personas Generation: A Comparative Analysis of Personality Representation and Censorship Effects
Automated Feedback to Students in Data Science Assignments: Improved Implementation and Results
A Multidisciplinary approach to plan ECOsystem SErvices for cities in Transition
VR-ISLAND: Virtual Reality, Inclusion and Special Language Needs
How Age Influences the Interpretation of Emotional BodyLanguage in Humanoid Robots
There is more in a single touch: mapping the continuous to the discrete