research

Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval

arXiv:2606.25237v1 Announce Type: cross Abstract: We develop accurate and efficient solutions for large-scale retrieval tasks where novel (zero-shot) items can arrive continuously at a rapid pace. Con

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Fault of Our Stars: Behavioral Drivers of Rating-Sentiment Incongruence

DGX agent

arXiv:2606.25518v1 Announce Type: new Abstract: When people share experiences online, they often express thoughts in two ways: a star rating and a written review. In sentiment analysis, ratings are wi

researcharxiv-cs-cl

25 Jun 2026

FDN: Interpretable Spatiotemporal Forecasting with Future Decomposition Networks

arXiv:2606.25201v1 Announce Type: new Abstract: Spatiotemporal systems comprise a collection of spatially distributed yet interdependent entities each generating unique dynamic signals. Highly sophist

FeVOS: Foresight Expression Video Object Segmentation

arXiv:2606.25585v1 Announce Type: new Abstract: Existing Referring Video Object Segmentation tasks focus on referring expressions describing events, actions or appearances of relevant objects within t

Frequency Domain Reservoir Computing

arXiv:2606.24969v1 Announce Type: new Abstract: While the quadratic sequence-length bottleneck of transformers has fueled a resurgence in recurrent models, effectively capturing complex dynamics requi

From Rubble Simulation to Active Magnetic Mapping: Quantum Sensing for Disaster Response

arXiv:2606.25957v1 Announce Type: new Abstract: Locating survivors of building collapses within the first 72 hours is a critical challenge in disaster response, and existing sensing modalities provide

FUTO Swipe: Layout-Agnostic Neural Swipe Decoding

arXiv:2606.25247v1 Announce Type: cross Abstract: Neural swipe decoders are typically tied to the keyboard they were trained on, requiring a new corpus and training run for each layout. In this report

Fuzzy Quantification over OWL Ontologies and Knowledge Graphs

arXiv:2606.25778v1 Announce Type: new Abstract: This paper presents a versatile framework for evaluating fuzzy quantification queries over both standard and fuzzy ontologies as well as knowledge graph

researcharxiv-cs-ai

Gastroendoscopy View Synthesis: A New Real Dataset and Evaluation

arXiv:2606.25427v1 Announce Type: new Abstract: Novel view synthesis (NVS) is an active research topic in computer vision, owing to the success of neural radiance field (NeRF) and 3D Gaussian splattin

Geo-Strat-RL: Learning Geological Event Reasoning from Verifiable Tasks

arXiv:2606.25000v1 Announce Type: new Abstract: To evaluate whether vision-language models can reason about geological histories, it is necessary to construct observations for which the underlying pro

GeoRanker: Distance-Aware Ranking for Worldwide Image Geolocalization

arXiv:2505.13731v4 Announce Type: replace Abstract: Worldwide image geolocalization-the task of predicting GPS coordinates from images taken anywhere on Earth-poses a fundamental challenge due to the

Gradient-based inverse lithography for EUV masks via the waveguide method and a physics-informed neural operator

arXiv:2606.25753v1 Announce Type: new Abstract: Gradient-based inverse lithography technology~(ILT) for extreme ultraviolet~(EUV) masks is presented. A novel framework treats the differentiable wavegu

GRAFT: Graph-Based Affordance Transfer via Part Correspondence

arXiv:2606.25241v1 Announce Type: new Abstract: Generalizing robotic manipulation to unseen objects remains challenging, as learning-based approaches require many demonstrations and fail in few-shot s

Graph it first! Enabling Reasoning on Long-form Egocentric Videos through Scene Graphs

arXiv:2606.25842v1 Announce Type: new Abstract: Existing multi-modal large language models (MLLMs) face significant challenges in processing long video sequences due to strict input token limitations.

GROVE: Grounded Pedestrian Simulation via Natural Language for Interactive Social Robot Navigation

arXiv:2606.25504v1 Announce Type: new Abstract: Pedestrian simulation is a critical component for training and deploying social robot navigation approaches, yet it remains a largely rigid system that

Heterogeneous and Adept Snapshot Distillation for 3D Semantic Segmentation

arXiv:2606.25278v1 Announce Type: new Abstract: Multi-modal fusion and multi-model ensembling are prevalent in enhancing the performance of 3D semantic segmentation. Despite the impressive performance

Holographic Memory for Zero-Shot Compositional Reasoning in Knowledge Graphs: A Mechanistic Study of Where and Why It Fails

arXiv:2606.24948v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) models predict single-hop links well but have no mechanism for zero-shot compositional queries: multi-hop questions whos

How Does the Pretraining Distribution Shape In-Context Learning? A Fundamental Trade-Off

arXiv:2510.01163v2 Announce Type: replace Abstract: The factors driving the performance of in-context learning (ICL) in large language models (LLMs) remain poorly understood despite ICL's surprising e

How Large Language Models Source Brand Reputation Across Languages and Markets

arXiv:2606.25787v1 Announce Type: cross Abstract: When a large language model (LLM) answers a question about a company, it grounds the answer in retrieved web sources, and those sources decide what th

How Modular Is a Frontier Mixture-of-Experts? A Pre-registered Causal Test in Which Apparent Expert Modularity Mostly Dissolves

arXiv:2606.25092v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models route each token to a few of many experts, inviting the hypothesis that experts form functional modules tied to c

Hybrid deep learning-based phase diversity method for wavefront reconstruction

arXiv:2606.25855v1 Announce Type: cross Abstract: The efficiency of high-power laser systems is limited by wavefront distortions in the beam, particularly non-common path aberrations, which reduce the

Hybrid-IR: Dual-Path Hybrid Retrieval with Iterative Reasoning for Complex Medical Question Answering

arXiv:2606.25338v1 Announce Type: new Abstract: Large language models (LLMs) have shown promising performance across a wide range of biomedical applications, including medical question answering (QA),

IBM has unveiled chip technology that could help extend Moore’s Law another decade

IBM has built a new prototype chip with around 100 billion transistors on an area the size of a fingernail, which is twice the density of the company’s previous state-of-the-art technology announced i

researchmit-tech-review

IBM introduces the smallest computer chip in the world

IBM announced the development of sub-1 nanometer computer chips, representing a significant advancement in semiconductor miniaturization beyond previous technological limits. This breakthrough in chip

researchibm-research

ILV: Iterative Latent Volumes for Fast and Accurate Sparse-View CT Reconstruction

arXiv:2603.14915v2 Announce Type: replace Abstract: A long-term goal in CT imaging is to achieve fast and accurate 3D reconstruction from sparse-view projections, thereby reducing radiation exposure,

Improved Large Language Diffusion Models

arXiv:2606.25331v1 Announce Type: new Abstract: Modern large language models are predominantly trained with autoregressive factorization and causal attention. We present iLLaDA, an 8B masked diffusion

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors

arXiv:2606.25971v1 Announce Type: new Abstract: Modern neural network training relies on optimizers such as Adam and Muon which act on each weight matrix as a single object. Yet every weight matrix ca

In-context Region-based Drag: Drag Any Region to Any Shape

arXiv:2606.25907v1 Announce Type: new Abstract: Diffusion models have shown promise in drag-style editing. Previous works mainly focus on point-based drag, which is inherently ambiguous. This paper fo

Independent analyses estimate that your actions to dismantle USAID and drastically reduce lifesaving foreign aid have already killed 700,000…

Independent analyses estimate that your actions to dismantle USAID and drastically reduce lifesaving foreign aid have already killed 700,000 people. Here are some of those people. 🧵https://x.com/elonm

researchyann-lecun--x

Introducing corpora Hlava Cor and Hlava AD: Human Label Variation in Coreference and Discourse Relations

arXiv:2606.25383v1 Announce Type: new Abstract: As previous research on annotator disagreement in discourse phenomena has shown, understanding text coherence varies considerably from one individual to

Invariant Kalman filtering for extended pose estimation in multi-IMU articulated rigid-body systems

arXiv:2606.25083v1 Announce Type: new Abstract: Accurate extended pose estimation (orientation, velocity, and position) for IMU-instrumented articulated rigid-body systems is a key challenge in roboti

Invisible to humans, visible to machines: a preregistered audit of Unicode fidelity across four biomedical bibliographic APIs

arXiv:2606.24897v1 Announce Type: cross Abstract: Biomedical text mining, scientometrics, and the construction of training corpora for biomedical large language models (LLMs) all assume that the abstr

Is Variational Monte Carlo Robust? Sharp Moment Thresholds and Heavy-tailed Stochastic Optimization

arXiv:2606.26009v1 Announce Type: new Abstract: Variational Monte Carlo (VMC) is a central algorithm in electronic structure theory and has gained renewed importance through modern neural-network ansa

It’s time for everyone to realize that the fight against data centers has nothing to do with data centers. They have become a proxy for the …

It’s time for everyone to realize that the fight against data centers has nothing to do with data centers. They have become a proxy for the hate towards AI and the concentration and accumulation of we

researchyann-lecun--x

Large-Scale Tunnel Air--Ground Collaboration With FLISP: Fast LiDAR-IMU Synchronized Path Planne

arXiv:2606.25393v1 Announce Type: new Abstract: Hydropower tunnel inspection is critical for infrastructure integrity yet remains inefficient and hazardous using manual methods. We propose FLISP (Fast

Latent Space Analysis for Interpretable Uncertainty in Melanoma Classification

arXiv:2506.18414v3 Announce Type: replace Abstract: Melanoma is a highly aggressive skin cancer, making early and accurate diagnosis critical. While deep learning excels in skin lesion classification,

Leaking Circuit Secrets: Gradient Leakage Attacks on Graph Neural Networks

arXiv:2606.25589v1 Announce Type: new Abstract: As graph neural networks (GNNs) become standard tools for critical tasks in circuit design and analysis, their security and privacy risks require carefu

Learning Non-Vacuous Generalization Bounds from Optimization

arXiv:2206.04359v3 Announce Type: replace Abstract: One of the fundamental challenges in the deep learning community is to theoretically understand how well a deep neural network generalizes to unseen

Learning Perceptive Platform Adaptive Locomotion Controllers for Quadrupedal Robots

arXiv:2606.25179v1 Announce Type: new Abstract: Universal quadrupedal locomotion remains limited by the difficulty of integrating perception across diverse robot morphologies. State-of-the-art control

Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models

arXiv:2504.09910v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a promising technique for applying LLMs to proprietary domains. However, retrieved documents may contain sen

Learning with Monotone Adversarial Corruptions

arXiv:2601.02193v2 Announce Type: replace Abstract: We study the extent to which standard machine learning algorithms rely on exchangeability and independence of data by introducing a monotone adversa

Limitations of SGD for Multi-Index Models Beyond Statistical Queries

arXiv:2602.05704v2 Announce Type: replace Abstract: Understanding the limitations of gradient methods, and stochastic gradient descent (SGD) in particular, is a central challenge in learning theory. T

LLM-ACES: Closed-Loop Discovery of Dynamical Systems with LLM-Guided Adaptive Search

arXiv:2606.25039v1 Announce Type: cross Abstract: Recovering governing Ordinary Differential Equations (ODEs) from data is a central challenge in modeling dynamical systems across scientific domains.

Logit Distance Bounds Representational Similarity

arXiv:2602.15438v3 Announce Type: replace Abstract: For a broad family of discriminative models that includes autoregressive language models, identifiability results imply that if two models induce th

Low-Cost High-Order Singular Value Decomposition for Tensor-Based Reconstruction from Sparse Sensor Measurements: Urban Flow and Air-Quality Applications

arXiv:2606.24989v1 Announce Type: new Abstract: Urban flow and air-quality simulations generate high-dimensional datasets describing velocity and pollutant transport across multiple spatial, temporal,

Measurable Majorities Are Not Finitely Axiomatizable

arXiv:2606.25954v1 Announce Type: cross Abstract: This theoretical note studies the finite axiomatizability of strict majority reasoning in finite social decision frames. Moss and Pedersen (2026) intr

researcharxiv-cs-ai

MIMFlow: Integrating Masked Image Modeling with Normalizing Flows for End-to-End Image Generation

arXiv:2606.26016v1 Announce Type: new Abstract: Normalizing Flows (NFs) are powerful generative models capable of exact density estimation and sampling. However, their strict invertibility often force

Minimalist Preprocessing Approach for Image Synthesis Detection

arXiv:2606.25297v1 Announce Type: new Abstract: Generative models have significantly advanced image generation, resulting in synthesized images that are increasingly indistinguishable from authentic o