Search: “research”

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). Wh…

Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). When the variables to be inferred are continuous, it makes sen

researchyann-lecun--x

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Research

Visual Distribution Anchoring for Efficient Prompt Tuning

DGX agent

arXiv:2607.28967v1 Announce Type: new Abstract: Prompt tuning adapts vision--language models with few trainable parameters, but existing approaches trade off efficiency and adaptation: static textual

researcharxiv-cs-cv

3 Aug 2026

VSTaI: Design and Characterization of Variable-Stiffness Tactile Interfaces Based on 3D-Printed Structured Fabrics

arXiv:2607.29102v1 Announce Type: new Abstract: Realistic palpation training requires reliable rendering of soft tissue stiffness changes in real time, which is difficult to achieve with conventional

Weight-Space Mixture-of-Experts for Implicit Neural Representation Classification

arXiv:2607.29463v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) encode signals as the weights of a coordinate-based neural network and have recently been proposed as an alternat

When Model Priors Conflict with Visual Evidence: Mitigating Commonsense-Driven Hallucinations by Selective Prior Calibration

arXiv:2607.29240v1 Announce Type: cross Abstract: In vision--language models, commonsense-driven hallucination (CDH) occurs when a model's commonsense prior overrides clear visual evidence of an atypi

ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification

arXiv:2607.28637v1 Announce Type: new Abstract: This paper presents our system for the CHiPSAL 2026 shared task on multimodal hate speech and sentiment detection in Nepali memes. We address both subta

More on the pelican on the bicycle test from @simonw: https://simonwillison.net/2025/Jun/6/six-months-in-llms/ I uploaded the source here so…

More on the pelican on the bicycle test from @simonw: https://simonwillison.net/2025/Jun/6/six-months-in-llms/ I uploaded the source here so it's playable in the browser, forkable etc. https://karpath

researchkarpathy--x

2 Aug 2026

To address the limits of deep learning and avoid stalling, the field of AI started by applying patch (1), which started being demoed 9 month…

researchfrancois-chollet--x

To address the limits of deep learning and avoid stalling, the field of AI started by applying patch (1), which started being demoed 9 months later in December 2024 and has now become completely ubiqu

2 Aug 2026

We're starting to leave the territory where you'd test an LLM by e.g. 'create an svg of pelican on a bicycle'. As one idea to generalize it,…

We're starting to leave the territory where you'd test an LLM by e.g. 'create an svg of pelican on a bicycle'. As one idea to generalize it, I was interested what Opus 5 would do if I gave it the firs

researchkarpathy--x

2 Aug 2026

4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans

arXiv:2607.27634v1 Announce Type: new Abstract: Generating high-quality 360-degree dynamic human assets from text prompts is challenging. Existing methods usually synthesize monocular or multi-view vi

A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation

arXiv:2607.27501v1 Announce Type: new Abstract: We present a lightweight approach to foundation modeling (extbf{NEXUS}) that leverages pre-trained learning from collider physics data towards out-of-do

A Montage-Agnostic Encoder for Calibration-Light Cross-User Gesture Recognition from Surface Electromyography

arXiv:2607.27565v1 Announce Type: new Abstract: Pattern-recognition control promises a myoelectric prosthesis that responds to many intended gestures rather than one or two, but the promise has stayed

Model Releases

A novel k-means clustering approach using two distance measures for Gaussian data

model-releasesarxiv-cs-lg

arXiv:2511.17823v2 Announce Type: replace Abstract: Clustering algorithms have long been the topic of research, representing the more popular side of unsupervised learning. Since clustering analysis i

A Reference-Free Score for Detecting Silent Reasoning Failures in Large Language Models

arXiv:2607.26102v1 Announce Type: cross Abstract: Mathematical chain of thought (CoT) evaluation is commonly reduced to whether the final answer matches a reference. This conflates producing a correct

A Sparse Glimpse of the Whole: Train-Free Self-Speculative Decoding

arXiv:2607.27735v1 Announce Type: new Abstract: Speculative decoding alleviates the memory-bandwidth bottleneck in large language model inference, but its acceleration is jointly constrained by drafti

Accelerating SGDM via Learning Rate and Batch Size Schedules: A Lyapunov-Based Analysis

arXiv:2508.03105v3 Announce Type: replace Abstract: We analyze the convergence behavior of stochastic gradient descent with momentum (SGDM) under dynamic learning-rate and batch-size schedules by intr

AdaAnchor4D: Anchor-Conditioned Spatiotemporal Feature Aggregation for Monocular UAV 4D Reconstruction

arXiv:2607.28320v1 Announce Type: new Abstract: Monocular UAV videos provide valuable observations for dynamic reconstruction of complex urban scenes. However, such scenes exhibit pronounced spatiotem

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

arXiv:2607.28617v1 Announce Type: cross Abstract: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout com

An analysis of binary isotonic regression: degrees of freedom and implications for calibration

arXiv:2607.27301v1 Announce Type: cross Abstract: Isotonic regression is a canonical tool for estimating monotone functions and calibrating probabilistic predictors. We provide a fully sharp finite-sa

An Efficient Solution to the 2D Visibility Problem in Cartesian Grid Maps and its Application in Heuristic Path Planning

arXiv:2403.06494v2 Announce Type: replace-cross Abstract: This paper introduces a novel, lightweight method to solve the visibility problem for 2D grids. The proposed method evaluates the existence of

ARCSnake V2: Mechanical Adaptations For An Amphibious Multi-Domain Screw-Propelled Snake-Like Robot

arXiv:2511.11970v2 Announce Type: replace Abstract: Robotic exploration in extreme environments, such as caves, oceans, and extraplanetary surfaces, poses significant challenges, specifically locomoti

Arm2Air: Cross-Embodiment Skeleton Transfer for 3D Relay Formation

arXiv:2607.27627v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) relay networks can restore connectivity after communication infrastructure is damaged. Urban relay placement is difficult

Articulated Object Reconstruction from Rest-State Observation

arXiv:2607.27749v1 Announce Type: new Abstract: Building interactive digital twins requires recovering both 3D geometry and the kinematic structures that govern how objects articulate. Yet existing me

Audio-Anchored Fusion of Multi-Ratio DiT Reconstruction Residuals for Cross-Domain Audio Deepfake Detection

arXiv:2607.26472v1 Announce Type: cross Abstract: Audio deepfake detectors often degrade when generators, corpora, or recording conditions change. We use a Diffusion Transformer (DiT), trained only on

AWARE-FX: An Auditable Knowledge-Guided AI System for Measuring Corporate Foreign-Exchange Hedging Disclosure

arXiv:2607.27611v1 Announce Type: new Abstract: Corporate annual reports contain weakly structured evidence about foreign-exchange risk management, derivative use, natural hedging, and explicit non-us

Balancing Privacy and Efficiency: Music Information Retrieval via Additive Homomorphic Encryption

arXiv:2508.07044v2 Announce Type: replace-cross Abstract: Modern music retrieval runs on vector embeddings, and once these embeddings are shared for search or matching they can be copied, probed, or u

Beyond a Single Judge: Simulating Social Persona Panels for Generative UI Evaluation

arXiv:2607.28439v1 Announce Type: new Abstract: Generative UI (GenUI) lets large language models synthesize a complete, renderable interface directly from a natural-language instruction, but evaluatin

Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures

arXiv:2607.28007v1 Announce Type: new Abstract: Pathology foundation models (FMs) are models trained on vast amounts of typically unlabeled data and have been shown to yield regularized latent spaces

Beyond Visual Ambiguity: Guiding Robust Monocular Depth Estimation in Challenging Scenarios via Detailed Long Captions

arXiv:2607.28285v1 Announce Type: new Abstract: Monocular depth estimation (MDE) faces challenges with non-Lambertian surfaces and adverse weather conditions due to the visual ambiguities inherent in

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

arXiv:2607.27700v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) suffer from prohibitive inference overhead due to long sequences of visual tokens. However, existing visual token re

Causal Discovery with Inverted Self-attention for Multivariate Time Series

arXiv:2607.28212v1 Announce Type: new Abstract: Causal discovery in multivariate time series data is challenging due to complex interactions, high dimensionality, and nonlinear dependencies among vari

Closed-Loop Bayesian Bandit Encoder with GRAND Receiver for a Bursty Interference Channel

arXiv:2607.15404v2 Announce Type: replace-cross Abstract: Interleaving mitigates burst errors but introduces decoding delay and removes temporal error structure that a channel-aware decoder could expl

Collaborative Feature Aggregation for Face Super-Resolution and Robust Re-Identification

arXiv:2607.28130v1 Announce Type: new Abstract: We propose a novel collaborative approach for face super-resolution (SR) and robust person re-identification from sequential or multi-view facial images

Compression-Based Behavioral Similarity for Open-World Sybil Discovery on Ethereum

arXiv:2607.27370v1 Announce Type: new Abstract: Sybil attackers are Blockchain actors that adopt the characteristics of regular users to exploit airdrops or influence governance. Current methods of Sy

Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech

arXiv:2607.26236v1 Announce Type: cross Abstract: AI-generated counterspeech offers a scalable and effective strategy to mitigate online toxicity by promoting more constructive dialogue. Yet, existing

Continual Learning with Vision-Language Models via Semantic-Geometry Preservation

arXiv:2603.12055v3 Announce Type: replace Abstract: Continual learning of pretrained vision-language models (VLMs) is prone to catastrophic forgetting, yet current approaches adapt to new tasks withou

Contrastive Concept Importance: Explaining Pairwise Class Decisions Through Automatically Extracted Concept Representations

arXiv:2607.27904v1 Announce Type: new Abstract: Concept-based explanations are a prevalent way to explain the decisions of complex black-box methods through semantically meaningful, human-interpretabl

Convolutional Neural Shading for High-Quality 3D Reconstruction from Multi-View Images

arXiv:2607.28132v1 Announce Type: new Abstract: We propose a convolutional neural shading (CNS), a novel pipeline to reconstruct high-quality 3D shapes from multi-view images. Several recent studies h

Cybersecurity Detection Classification with Reasoning-enabled Language Models

arXiv:2607.28460v1 Announce Type: new Abstract: A major issue in Security Operations Centers (SOCs) is alert fatigue, as the number of detections reported is more than staff can triage in a given day.

Decision-oriented joint optimization of evidence fusion based on event-conditioned credibility

arXiv:2504.04128v3 Announce Type: replace Abstract: In decision-level fusion tasks involving heterogeneous sources with unequal precision and potential anomalies, evidence deviating from the majority

Deep learning-based hierarchical insect classification using camera trap imagery

arXiv:2607.28005v1 Announce Type: new Abstract: Declining insect populations make reliable biodiversity monitoring increasingly urgent, yet monitoring of insect biodiversity is hampered by a lack of s

Direct Rotor Thrust Sensing and Feedback Control for Disturbance Rejection of Multirotors Using Load-cells

arXiv:2607.10099v2 Announce Type: replace Abstract: Gust disturbances, dynamic vertical inflow and ground effect are key adverse aerodynamic phenomena that induce variations in the forces acting on a

Distributions In, Distributions Out: The Case for Soft-Label Training

arXiv:2511.14117v2 Announce Type: replace Abstract: Supervised classifiers output a distribution over classes but are typically trained against a single label obtained by collapsing multiple annotator

Doubly Robust Functional Representation Learning for Longitudinal Causal Inference with Irregular Histories

arXiv:2607.28567v1 Announce Type: cross Abstract: Longitudinal causal studies often record histories as irregular functional fragments: laboratory values, physiologic signals, sensor streams, and imag

Driving up Inference Energy on SNNs: Per-Sample and Universal Sponge Attacks

arXiv:2607.27990v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) communicate through sparse binary spike events rather than dense activations, enabling energy-efficient inference on ne

ENCORE: Event-Assisted Complementary Motion Refinement for Learned Video Compression

arXiv:2607.28020v1 Announce Type: new Abstract: Learned video compression relies on accurate temporal modeling to remove redundancy between adjacent frames. However, most existing codecs infer motion

Encryption-Compatible Clustered Federated Learning via Distributed Expectation-Maximization over Metadata

arXiv:2607.28338v1 Announce Type: new Abstract: Clustered Federated Learning (CFL) addresses data heterogeneity in federated settings by grouping clients with similar data distributions to enable effe

Endo-NeRF++: Uncertainty-Aware Neural Rendering with Multi-Resolution Hash Encoding for Dynamic Surgical Scene Reconstruction

arXiv:2607.27825v1 Announce Type: cross Abstract: Reconstructing dynamic surgical scenes is crucial for robot-assisted minimally invasive surgery; however, it continues to be difficult because of tiss