Search: “models”

Surface Reconstruction from Range Scans Under Visibility Constraints

arXiv:2610.18005v1 Announce Type: new Abstract: Surface reconstruction from range scans is challenging in the presence of noise and outliers, as fidelity to observations must be balanced against sensi

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Swarm Telepathy: Prefill-Free KV-Cache Transfer Across Families

DGX agent

arXiv:2610.15095v1 Announce Type: new Abstract: LLM multi-agent systems split work across agents that communicate through text. An agent summarizes its findings, another agent receives the text. This

hardwarearxiv-cs-lg

14 Oct 2026

TableVision: Recovering Verified Structure from Historical Tables

arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and

Terrain-Aided Navigation Without Raycasting: A Sliding Grid Approach for Point Cloud Processing

arXiv:2510.06470v2 Announce Type: replace-cross Abstract: We investigate the use of a point cloud measurement in terrain-aided navigation. Our goal is to aid an inertial navigation system, by explorin

hardwarearxiv-cs-ro

Text-Only vs. Image-Aware VLM Judges for Manga Translation Evaluation

arXiv:2610.17908v1 Announce Type: cross Abstract: In manga translation, visual context outside speech-bubble text, including speaker identities, referents, and scene tone, is depicted in page images,

The RNN Homunculus: Learning to Gate Long-Term Memory

arXiv:2610.14279v1 Announce Type: new Abstract: Learning long-range dependencies with recurrent neural networks (RNNs) is difficult because of the vanishing gradient problem. Gated recurrent neural ne

tutorialsarxiv-cs-lg

Totem: Object-Centric 3D Memory for World-Consistent Video Generation

arXiv:2610.15807v1 Announce Type: new Abstract: Generating coherent videos grounded in a unified underlying world remains a major challenge, particularly under large viewpoint changes, where existing

Applications

Towards Privacy-Preserving Thermal Human Perception from Dataset to Deployment

arXiv:2610.14846v1 Announce Type: new Abstract: Indoor human perception is the foundation for smart homes and healthcare. However, RGB cameras raise privacy concerns in private indoor environments, wh

applicationsarxiv-cs-cv

Training-Free Multi-Agent Cooperative Embodied Search from Uncertain Vision-Language Priors

arXiv:2610.15038v1 Announce Type: new Abstract: Real-world Vision-Language Navigation (VLN) requires agents to act under partial observability, where map structure, semantic cues, and target locations

safetyarxiv-cs-ro

TrajCFG: Token-Wise Classifier-Free Guidance via Denoising Trajectory Feedback

arXiv:2610.14153v1 Announce Type: new Abstract: Classifier-free guidance (CFG) typically applies a shared scale to all latent tokens, although their velocity predictions evolve differently during samp

Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective

arXiv:2610.14394v1 Announce Type: cross Abstract: Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions,

Unravel: Recovering an Interactive 3D Scene from a Single Image

arXiv:2610.16146v1 Announce Type: new Abstract: We present Unravel, a training-free framework that turns a single image into an interactive 3D scene, where every object is an independent and movable a

agentsarxiv-cs-cv

Local Ai

Using Line Segment Tracking to enable ML-based Track Reconstruction in CMS

arXiv:2610.15963v1 Announce Type: cross Abstract: High-pileup conditions in CMS during the HL-LHC era make charged-particle tracking increasingly challenging as detector occupancy and combinatorics gr

local-aiarxiv-cs-lg

Visual Sevoing from Lines

arXiv:2610.18363v1 Announce Type: cross Abstract: In this work, we present a fundamentally new approach to visual servoing using lines. It is based on a theoretical and geometrical study of the main l

safetyarxiv-cs-cv

Walk Like This: Stylized Locomotion for Physics-Based Characters through Example-Driven Diffusion

arXiv:2610.18147v1 Announce Type: new Abstract: We present a real-time framework for expressive legged locomotion that enables independent control over velocity and style. Unlike existing data-driven

researcharxiv-cs-ro

What Makes a Latent Space Shared? Direct and Recoverable Compatibility in Motion VAEs

arXiv:2610.17376v1 Announce Type: cross Abstract: A shared latent space is often assumed to make representations from different schemas directly interchangeable, yet sharing parameters, dimensionality

safetyarxiv-cs-cv

When Does Compensating Inherited Quantization Error Help? Mean-Square Guarantees for Layer-Wise Quantization and Their Limits

arXiv:2610.16020v1 Announce Type: new Abstract: Layer-wise post-training quantization methods let each layer compensate for the quantization error inherited from earlier layers. We ask under what assu

WorldRoPE: Probabilistic World-Centric Rotary Embedding for Multi-View Attention

arXiv:2610.16337v1 Announce Type: new Abstract: Rotary Positional Embedding (RoPE) is widely used to encode relative positions in Transformers. In multi-view settings, however, patch coordinates are d

Local Ai

b11586: cuda : warnings cleanup (#30420)

local-aillama-cpp-releases

cuda : warnings cleanup Signed-off-by: Adrien Gallouët angt@huggingface.co Update ggml/src/ggml-cuda/common.cuh Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaeret@huggingface.co Signed-off-by: Adrien

Machine Learning Tutorial/Workshop [D]

tutorialsr-machinelearning

This post is to let people know about a workshop/tutorial on Machine Learning that will run on the (blue) math discord server: discord.gg/maths. The place is nice, people are cool and helpful, and as

NVIDIA Run:ai Is Now Open Source as Part of NVIDIA DSX AI Factory Platform

On October 13, 2026 NVIDIA released the complete Run:ai platform—an AI workload and GPU orchestration system—as open‑source software under its DSX AI Factory Platform. The modular release includes fou

hardwarenvidia-developer

Scaling AI-driven chip design with open agent factories

IBM Research has presented a new approach that scales AI‑driven chip design by employing open “agent factories,” lowering inference cost by 11.5 × compared to fully proprietary setups. The method enab

agentsibm-research

Local Ai

Agentic Peer-to-Peer Networks: From Content Distribution to Capability and Action Sharing

arXiv:2603.03753v2 Announce Type: replace-cross Abstract: The ongoing shift of Artificial Intelligence (AI) from centralized cloud application programming interfaces (APIs) to local inference on edge

local-aiarxiv-cs-ai

Approximation of differential entropy in Bayesian optimal experimental design

arXiv:2510.00734v2 Announce Type: replace-cross Abstract: Bayesian optimal experimental design provides a principled framework for selecting experimental configurations that maximize obtained informat

Beyond Semantic IDs: Finite-Beam Reachability and Continuous-Query Generation in Generative Recommendation

arXiv:2610.12977v1 Announce Type: new Abstract: Generative recommendation (GR) of social media platforms commonly retrieves items by autoregressively decoding discrete Semantic IDs (SIDs) with finite-

researcharxiv-cs-ai

Beyond the Snowflakes: Disentangling Weather Effects from Confounding Meta-Factors in LiDAR Object Detection

arXiv:2610.13891v1 Announce Type: cross Abstract: Light Detection and Ranging (LiDAR) is critical for autonomous perception, yet its performance is known to degrade in adverse weather. While existing

agentsarxiv-cs-ro

Breaking the Cloak! Unveiling Chinese Cloaked Toxicity with Homophone Graph and Toxic Lexicon

arXiv:2505.22184v3 Announce Type: replace-cross Abstract: Social media platforms have experienced a significant rise in toxic content, including abusive language and discriminatory remarks, presenting

researcharxiv-cs-ai

CliQ-RRG: Clinical-Knowledge Guided Disease-aware Visual-Textual Alignment for QA-Style Radiology Report Generation

arXiv:2610.13059v1 Announce Type: new Abstract: Radiology reports are essential for diagnostic reasoning and patient care, yet their manual preparation is time-consuming and cognitively demanding. Aut

safetyarxiv-cs-cl

Controlled-Minimax: Stabilizing Adversarial Optimization via Control Theory

arXiv:2610.12915v1 Announce Type: new Abstract: Minimax optimization is fundamental to adversarial learning yet suffers from severe stability challenges, often manifesting as persistent limit cycles o

Decoding Register Tokens Preserves Global Scene Details

arXiv:2610.13299v1 Announce Type: cross Abstract: Pretrained vision transformers learn structured image representations spanning spatial patch tokens and non-spatial tokens. Recent analyses suggest th

tutorialsarxiv-cs-lg

DeFiRank: Federated Pairwise Ranking for Governance in Decentralized Financial Networks

arXiv:2610.12916v1 Announce Type: new Abstract: Existing governance approaches in decentralized financial networks rely on manual review processes conducted by human committees, which introduces subje

safetyarxiv-cs-ai

Applications

Easy-IIL: Reducing Human Operational Burden in Interactive Imitation Learning via an Assistant Expert

arXiv:2603.12769v2 Announce Type: replace Abstract: Interactive Imitation Learning (IIL) typically relies on extensive human involvement for both offline demonstration and online interaction. Prior wo

applicationsarxiv-cs-ro

Equal-Budget Monte Carlo Tree Search versus Randomized-Restart List Scheduling for DAG Workflows: A Controlled Equal-Budget Computational Study

arXiv:2610.12542v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) is often proposed for scheduling directed-acyclic-graph (DAG) workflows, yet most studies never run the comparison that c

researcharxiv-cs-ai

Fear Is Not Always Fear: Variation in Emotion Label Equivalence Across Datasets

arXiv:2610.12841v1 Announce Type: new Abstract: Emotion classifiers are routinely applied beyond their training data, on the assumption that same-named labels such as fear or surprise mean the same th

researcharxiv-cs-cl

Hidden Data Challenges in Clinical Machine Learning

arXiv:2610.13350v1 Announce Type: new Abstract: Widely reused preprocessing pipelines for electronic health records can encode assumptions about when information became available, what clinical episod

safetyarxiv-cs-lg

HorizonNav: Geometry-Guided Video Diffusion for Anticipatory 3D Robot Navigation

arXiv:2610.13849v1 Announce Type: new Abstract: We present HorizonNav, a video diffusion-based framework for anticipatory robot navigation that transforms a single RGB image and a text prompt into a g

safetyarxiv-cs-ro

Humanize MLE Agents: Multi-Agent Session Alternation Beyond Single-Agent Limits

arXiv:2610.13494v1 Announce Type: new Abstract: Existing LLM-based agent approaches for long-horizon machine learning engineering (MLE) often use context engineering, implemented through custom harnes

agentsarxiv-cs-ai

Hyper Algorithm Design Agent: Evolving Learnable Optimizer from Zero

arXiv:2609.35328v2 Announce Type: replace Abstract: Meta-Black-Box Optimization (MetaBBO) is one of the highlights in the recent AI for Optimization trend. This paradigm's bi-level workflow leverages

safetyarxiv-cs-ai

Infinite-Dimensional Closed-Loop Inverse Kinematics for Soft Robots via Neural Operators

arXiv:2602.18655v3 Announce Type: replace Abstract: For fully actuated rigid robots, kinematic inversion is a purely geometric problem, efficiently solved by closed-loop inverse kinematics (CLIK) sche

tutorialsarxiv-cs-ro

JoyInside-VLM-Agent: Product-Conditioned Multimodal Policy Learning for Embodied Agents

arXiv:2610.12957v1 Announce Type: cross Abstract: Embodied agents must translate multimodal observations and user requests into executable actions while adapting to product constraints, changing goals

safetyarxiv-cs-ai

Microsoft’s new AI chip makes it less reliant on Nvidia’s GPUs

Microsoft is announcing its third-generation Maia in-house AI chip today, designed to be the 'primary AI inference system' for Microsoft's products and services. Maia 300 not only improves the cost an

hardwarethe-verge-ai

Multi-Stream Attention Residuals

arXiv:2610.13630v1 Announce Type: new Abstract: Attention Residuals (AttnRes) enables content-dependent retrieval over network depth, which can be viewed as single-stream softmax attention along the d

researcharxiv-cs-cl

Neuromorphic Satellite Intelligence: A Formal Framework for Event-Driven Architectures, Spike-Based Algorithms, and Quantitative Energy-Accuracy Trade-offs

arXiv:2610.12471v1 Announce Type: cross Abstract: Satellite onboard computing faces an irreducible tension: mission intelligence requirements grow monotonically while power, mass, and radiation budget

hardwarearxiv-cs-lg

Applications

Orthros: Phase-Aware Heterogeneous Attention for Efficient Transformers

arXiv:2610.13735v1 Announce Type: cross Abstract: Efficient attention mechanisms, such as linear and sliding window attention, aim to reduce the computational complexity of Transformers from quadratic

applicationsarxiv-cs-ai

PACT: Privileged Trace Co-Training for Multi-Turn Tool-Use Agents

arXiv:2606.16215v2 Announce Type: replace-cross Abstract: Multi-turn tool-use agents must reason, call tools, and adapt to observations across several interaction turns. Post-training such agents is c

agentsarxiv-cs-ai

Polyconvex neural-network surrogates with learned paired directional features for anisotropic hyperelastic homogenization

arXiv:2610.12801v1 Announce Type: cross Abstract: Approximating the effective anisotropic hyperelastic response of a representative volume element (RVE) requires constitutive expressiveness, mechanica

ProgramGym: Scaling Training Environments for Long-Horizon Program Reproduction Agents

arXiv:2610.13395v1 Announce Type: cross Abstract: Coding agents are increasingly used to build programs from scratch as software engineers do rather than to resolve issues within a repository or to ge

agentsarxiv-cs-ai

Rationally Linearized MLPs

arXiv:2610.13568v1 Announce Type: new Abstract: We present Rationally Linearized Multilayer Perceptrons(RaLiMPs), a new approach to efficiently linearizing MLPs using low-degree rational approximation