Search: “model-releases”

Contact Trajectory Prompting: In-Context Transfer of Contact-Rich Behaviors from a Single Demonstration

model-releasesarxiv-cs-ro

arXiv:2610.18848v1 Announce Type: new Abstract: In-context robot learning enables robots to acquire new behaviors from demonstrations without test-time parameter updates. However, visual and kinematic

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Model Releases

Context-Aware Precision Scheduling for Small Language Models

DGX agent

arXiv:2610.15640v1 Announce Type: new Abstract: Small language models (SLMs) used as on-device agents must balance accuracy and latency as their context grows. Mixed precision helps manage this tradeo

model-releasesarxiv-cs-lg

14 Oct 2026

Continuous-Time Cloth Dynamics with Physics-Informed Neural ODEs

arXiv:2610.14342v1 Announce Type: new Abstract: We present ContinuousCloth, a continuous-time, physics-informed neural solver for deformable cloth dynamics that enforces a spring--mass ODE within a ne

corporate espionage they say

openai staff are out there turning the office into a stealth game, while my biggest security threat is letting codex, claude code and sumus loose on a test branch without read only permissions enabled

model-releasesr-chatgpt

Correcting or Continuing? What On-Policy Distillation Learns from Student Errors

arXiv:2610.18011v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts under a frozen teacher, mitigating the distribution mismatch of off-policy supervision

Correlation-Aware Reconstruction for Multivariate Time Series Anomaly Detection

arXiv:2610.15250v1 Announce Type: new Abstract: Reconstruction-based detectors for multivariate time series anomaly detection typically learn a single entangled representation of normal behavior and f

Counting with Attention and LayerNorm: Norm Scaling and Representation Geometry

arXiv:2610.16653v1 Announce Type: new Abstract: Counting is a simple task on which transformers can nevertheless fail at long sequence lengths. We study the cost of counting in a single attention laye

Cross-Market Meta-Learning for Electricity Price Forecasting

arXiv:2610.17387v1 Announce Type: new Abstract: Day-ahead (DA) electricity price forecasting is usually posed per market, with a separate model fitted to each grid's own history. This caps accuracy: s

CrossMean: Model Merging by Pairing Merged and Expert Activations

arXiv:2610.14762v1 Announce Type: new Abstract: Model merging combines fine-tuned experts into one network without retraining, and closed-form methods compute each merged layer from statistics of its

CryptoFlowBench: Benchmarking Multi-Hop Reasoning on Blockchains for Cryptocurrency Fund Tracing

arXiv:2610.16449v1 Announce Type: cross Abstract: Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows. Existing Graph Neur

cuda, hip: GDN chunked kernel by am17an · Pull Request #29353 · ggml-org/llama.cpp

model-releasesr-localllama

Performance on Model Prompt tokens master tok/s pr tok/s Change RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 2048 13,653.58 16,459.56 +20.6% RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 4096 14,090.26 1

D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control

model-releasesarxiv-cs-ro

arXiv:2610.17114v1 Announce Type: new Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, hel

D^{2}-VPR: A Parameter-efficient Visual-foundation-model-based Visual Place Recognition Method via Knowledge Distillation and Deformable Aggregation

arXiv:2511.12528v5 Announce Type: replace Abstract: Visual Place Recognition (VPR) aims to determine the geographic location of a query image by retrieving its most visually similar counterpart from a

Data Free Training of Diffusion Models for Lattice Field Theories

arXiv:2610.18863v1 Announce Type: cross Abstract: Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative s

Data-Topology Compatibility Enables Personalization in Decentralized Learning

arXiv:2610.15126v1 Announce Type: cross Abstract: Decentralized learning must balance collaboration with personalization across heterogeneous agents. This paper studies when cooperation can support st

DDVR-Net: Degradation-Aware Decoupling and Visibility-Guided Restoration for Historical Document Recognition

arXiv:2610.16956v1 Announce Type: new Abstract: Historical document analysis is crucial for cultural heritage preservation and low-resource language digitization. However, real historical documents of

Decoupling Knowledge Forgetting and Refusal Learning in MLLM Unlearning

arXiv:2610.14605v1 Announce Type: cross Abstract: Current evaluations of multimodal unlearning typically focus on whether a model stops outputting target information. This surface-level criterion, how

Deep Jump Gaussian Processes for Surrogate Modeling of High-Dimensional Piecewise Continuous Functions

arXiv:2510.21974v3 Announce Type: replace Abstract: We introduce Deep Jump Gaussian Processes (DJGP), a novel method for surrogate modeling of a piecewise continuous function on a high-dimensional dom

Deficit-Driven Stratified Acquisition for Building STRATA-S12: An Open SAR-Optical Corpus for Self-Supervised Learning

arXiv:2610.17680v1 Announce Type: cross Abstract: Building a co-registered SAR-optical corpus for self-supervised Earth Observation is above all an acquisition problem, yet the main multi-modal datase

DeltaTTG: Training Multi-Turn Agents with a Token-to-Go Progress Meter

arXiv:2610.17666v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) for multi-turn agents relies on sparse terminal rewards that say little about individual steps. Wi

Dependency, Compression, and Synergy: A Unified Information-Theoretic View of Multimodal Learning

arXiv:2609.14421v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models have intensified the need to understand how different modalities share, preserve, and complement infor

Depth Memory

arXiv:2610.18809v1 Announce Type: new Abstract: Residual connections propagate information through a network by additively accumulating layer outputs. Recently proposed alternatives, such as Manifold-

DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment

arXiv:2610.16278v1 Announce Type: new Abstract: Existing-image self-tiling aims to transform a given image into a seamlessly repeatable tile while preserving its original semantics and local details.

Diagnose-to-Generate: Eliminating Structural Distortions in Flow Models via Patch-Level Grounded Alignment

arXiv:2610.17882v1 Announce Type: new Abstract: Flow-based image generators achieve strong semantic synthesis but still produce localized structural distortions, such as malformed hands and limbs. Exi

Diagnosing Generalization Boundaries in AI-Based Vulnerability Detection via Calibrated Embedding Distances

arXiv:2610.14296v1 Announce Type: cross Abstract: High benchmark scores in learning-based vulnerability detection mask severe degradation under distribution shifts. This paper demonstrates that calibr

Discover AI: A Learning Guide - 51 hands-on labs for learning how AI actually works.

model-releasesr-localllama

This is an offline app with 51 hands-on labs for learning how AI actually works, from neurons to agents and more... **A bit of insight** - 51 labs in 6 groups, from the basics (what a neuron is, gradi

Distill3R: A Pipeline for Democratizing 3D Foundation Models on Commodity Hardware

arXiv:2602.00865v2 Announce Type: replace Abstract: While multi-view 3D reconstruction has shifted toward large-scale foundation models capable of inferring globally consistent geometry, their relianc

Do Artificial Neural Networks Need Dendritic Nanotubes? Two Reasons for Shrinking Importance Estimates in Continual Learning

arXiv:2610.14258v1 Announce Type: new Abstract: Regularization-based continual learning protects each parameter in proportion to an estimate of its importance, yet these estimates come from finite sam

Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional Languages

arXiv:2610.14112v1 Announce Type: cross Abstract: Calibrated typed-decision ('System One') models return a label and a probability in a single forward pass at a small fraction of the cost of large lan

Dog-Breed Text-to-image Flow Matching from Pretraining to Fine-Tuning on 4 Consumer GPUs

arXiv:2610.18870v1 Announce Type: new Abstract: We generally perceive that training text-to-image diffusion models requires heavy compute: it is true if we aim at a comprehensive frontier model. This

DoSA: Dots Sparse Attention

arXiv:2610.13990v1 Announce Type: new Abstract: Sparse attention visits few keys, yet finding them can still require scoring every key with every indexer head. We introduce DoSA (Dots Sparse Attention

DRNOISE: Benchmarking Deep Research Agents in Misleading Evidence Environments

arXiv:2607.17291v2 Announce Type: replace Abstract: Deep research agents increasingly operate over the open web, where relevant records coexist with redundant summaries, outdated reports, and misleadi

DSM-Free UAV Visual Localization via Latent-Depth Variable Projection and Structure-Adaptive Coupling

arXiv:2610.14945v1 Announce Type: new Abstract: Visual localization enables unmanned aerial vehicles (UAVs) to maintain absolute positioning in GNSS-denied environments. A common approach matches UAV

DuplexBridge: Coordinating Understanding and Generation for Unified Image Editing

arXiv:2610.18819v1 Announce Type: new Abstract: Complex image editing requires faithful task interpretation and accurate execution, but a failed edit does not reveal which responsibility failed. We pr

DuSRFlow: Dual-Lens Super-Resolution via Parallax-Aware Flow Estimation and Complementary Reference Warping

arXiv:2610.14630v1 Announce Type: new Abstract: Dual-lens super-resolution (DuSR) aims to enhance a wide-angle low-resolution (LR) image by exploiting a telephoto reference (Ref) image. A central chal

Dynamic Interpolation for Training-Time Prediction Reshaping in Low-Light Image Enhancement

arXiv:2610.18018v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) is an important image/video processing problem for reliable visual systems under poor illumination, yet it remains ch

Dynamic K-Head: Difficulty-Supervised Budget Selection for Continuous Latent Reasoning

arXiv:2610.17679v1 Announce Type: new Abstract: Chain-of-thought (CoT) improves reasoning but incurs substantial autoregressive rationale cost. Continuous CoT moves intermediate computation into recur

e1: Learning Adaptive Control of Reasoning Effort

arXiv:2510.27042v3 Announce Type: replace-cross Abstract: Increasing the thinking budget of AI models can significantly improve accuracy, but not all questions warrant the same amount of reasoning. Us

ECLIPTICA -- A Framework for Switchable LLM Alignment via CITA - Contrastive Instruction-Tuned Alignment

arXiv:2601.06157v2 Announce Type: replace Abstract: Alignment in large language models (LLMs) is still largely static: after training, the policy is frozen. DPO, GRPO methods typically imprint one beh

Effect of Spherical Parameter Space on Number of Non-Forgetting Tasks and Capacity of Continual Learning

arXiv:2610.17453v1 Announce Type: new Abstract: We propose a continuous learning formulation for T non-forgetting tasks with the spherical parameter space S^{d-1}(sqrt{d}) in asymptotic regime drighta

Efficient Resource-Shiftable RL Post-training with Generative Rewards

arXiv:2610.16866v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training with generative reward models (GenRM) has become a central recipe for improving large language models (LLMs),

Efficient Scene-Text Refinement via Pixel-Space Grouped Image Generation

arXiv:2610.18284v1 Announce Type: new Abstract: Generated images often have coherent layouts and visual content, yet local errors in small text and complex characters still limit their readability and

EgoOmniWorld: Unifying Egocentric Understanding via Ego-Action-World Interactions

arXiv:2610.18499v1 Announce Type: new Abstract: Egocentric video understanding spans diverse capabilities, modalities, and evaluation formats, yet these are often studied in isolation despite their ti

EgoProbe: Benchmarking Long-Range and Exact Memory in Streaming Egocentric Videos

arXiv:2610.17128v1 Announce Type: new Abstract: Egocentric video provides a continuous first-person record of everyday activities, making it a natural foundation for wearable AI assistants. Unlike off

EgoWholeView: Camera-Only Head-Mounted Capture of Body and Bimanual Hand Motion for Embodied Demonstrations

arXiv:2610.16256v1 Announce Type: new Abstract: Head-mounted body and bimanual motion capture supports self-avatars, teleoperation, and embodied demonstrations. However, a single egocentric camera is

ELECT: Settling Identity Before Rendering for Scalable Story Visualization

arXiv:2610.15555v1 Announce Type: new Abstract: Training-free story visualization without reference images must preserve recurring entities across frames while scaling to long narratives. Existing met

Elephant in the Fridge: Constant-Memory Frame Packing for Long Video Understanding

arXiv:2610.16118v1 Announce Type: new Abstract: Hour-long videos, streaming feeds, and movie-length content are pushing vision-language models (VLMs) past their breaking point -- the standard recipe o

Ellipsoids from Tangents

arXiv:2610.15580v1 Announce Type: new Abstract: This paper presents an algorithm for detecting and fitting multiple ellipsoids in 2D, 3D and higher-dimensional data. The representation is based on tan