Deep Residual Learning for Image Recognition
Official Best Paper · SourceShortcut connections let a network learn changes relative to its input, helping optimize deeper networks.
TOP CONFERENCE PAPERS
Top Conference Papers
Explore sourced AI research by conference, year, and recognition. Official awards include evidence; EyeCode Pick is a separate editorial selection.
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PAPER LIBRARY
CVPR · 2026
Attention is All you Need
The Transformer uses attention to model sequences without recurrent or convolutional networks.
LOAM: Lidar Odometry and Mapping in Real-time
Separates fast motion estimation from slower mapping to process LiDAR measurements in real time.
Indiscernible Object Counting in Underwater Scenes
EyeCode Pick · editorial selectionStudies counting hard-to-distinguish objects in underwater scenes and introduces the IOCfish5K dataset.
Transformers are Inherently Succinct
Official Outstanding Paper · SourceStudies how compactly Transformers represent formal languages. The proofs compare their representation size with automata and temporal logic, while exposing the computational difficulty of model verification.
LLMs Get Lost In Multi-Turn Conversation
Official Outstanding Paper · SourceExamines failures when instructions arrive over multiple conversation turns. Simulated conversations separate task aptitude from reliability and trace how premature assumptions affect later responses.
The Polar Express: Optimal Matrix Sign Methods and their Application to the Muon Algorithm
Official Honorable Mention · SourceComputes the matrix polar decomposition used by Muon. Minimax-designed polynomial iterations use GPU-friendly matrix multiplications, with analysis of approximation error and finite-precision behavior.
Safety Alignment Should be Made More Than Just a Few Tokens Deep
Official Outstanding Paper · SourceInvestigates safety alignment concentrated in the first output tokens. Case studies and regularized fine-tuning objectives explore deeper alignment and its persistence under subsequent fine-tuning.
Data Shapley in One Training Run
Official Honorable Mention · SourceAttributes training data contributions to a particular model run. It accumulates Shapley values of gradient updates rather than repeatedly retraining models on different data subsets.
SAM 2: Segment Anything in Images and Videos
Official Honorable Mention · SourceExtends promptable segmentation from images to video. A Transformer with streaming memory works with an interactive data engine to maintain prompted object masks across frames.
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
Official Best Paper · SourceStudies network depth in self-supervised goal-conditioned reinforcement learning. Locomotion and manipulation experiments examine how deep residual architectures and training scale affect goal-reaching behavior.
Why Diffusion Models Don’t Memorize: The Role of Implicit Dynamical Regularization in Training
Official Best Paper · SourceSeparates the onset of useful diffusion generation from later training-data memorization. Experiments and a random-features model analyze how training dynamics create a window of generalization before memorization.
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators
Official Best Paper · SourceAddresses the cost of high-order differential operators in neural networks. Taylor-mode automatic differentiation and randomized tensor contractions estimate operators for applications such as physics-informed neural networks.
Conformal Prediction as Bayesian Quadrature
Official Outstanding Paper · SourceRevisits conformal prediction from a Bayesian perspective on deployment risk. Bayesian quadrature represents plausible test-loss distributions beyond the information conveyed by frequentist guarantees alone.
Efficiently Reconstructing Dynamic Scenes One D4RT at a Time
Best Paper · CVPR 2026 · SourceCombines depth, spatiotemporal correspondence, and camera estimation from dynamic video. A unified point-query interface replaces separate task decoders in a feed-forward approach to 4D scene reconstruction.
3D Student Splatting and Scooping
Best Paper Honorable Mention · CVPR 2025 · SourceRevisits mixture representations in 3D Gaussian Splatting. Student distributions with positive and negative densities, together with a sampling-based optimizer, explore scene representations beyond conventional Gaussian components.
Spatially-Varying Autofocus
Official Honorable Mention · SourceStudies spatially selective focusing at different image locations. A Lohmann lens and phase-only spatial light modulator combine with contrast and disparity cues to iteratively adjust the focus map.
OmniRetarget: Interaction-Preserving Data Generation for Humanoid Whole-Body Loco-Manipulation and Scene Interaction
Official Best Paper · SourceRetargets human motion to humanoids while preserving body–object–terrain relationships. An interaction mesh and kinematic constraints generate and augment motion data for loco-manipulation.
MAC-VO: Metrics-aware Covariance for Learning-based Stereo Visual Odometry
Official Best Paper · SourceIntroduces metric-aware uncertainty to stereo visual odometry. Learned covariance guides keypoint selection and residual weighting, connecting image-matching reliability with pose-graph optimization.
Interdigitated Electrodes for Selective Stimulation of Skeletal Muscle Actuators in Biosyncretic Robots
Official Best Paper · SourceStudies selective control of skeletal-muscle actuators in biosyncretic robots. Optimized thin-film interdigitated electrodes target different muscle regions to support coordinated actuation.
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