model releases

Beyond Masked Sparsity: SNACK Enables Truly Sparse Neural Networks on GPU

arXiv:2610.04093v1 Announce Type: new Abstract: Deep neural networks continue to grow in parameter count, driving up training and inference cost on GPUs. Sparse neural networks and Dynamic Sparse Trai

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Model Releases

Beyond Overparameterization: Provable Learning of Input-Convex Multi-Layer Polynomial Networks with Active Queries

DGX agent

arXiv:2610.04999v1 Announce Type: new Abstract: The theoretical understanding of multi-layer neural networks is largely confined to overparameterized settings, which obscure parameter identifiability

model-releasesarxiv-cs-lg

6 Oct 2026

Beyond Plausibility: Verifiable Fine-Grained Image Editing on Structured Assets

arXiv:2610.04381v1 Announce Type: new Abstract: Fine-grained image editing requires more than producing a visually plausible result: an editor must execute the requested attribute change precisely whi

Beyond Transport Cost: Routing Differences between Flow Matching and Optimal Transport

arXiv:2610.05921v1 Announce Type: cross Abstract: In generative models, Optimal Transport (OT) is used to improve Flow Matching (FM) by reducing noise-data coupling cost. However, different noise-to-o

BossouChimpanzee: Long-term Chimpanzee Video Dataset

arXiv:2610.05293v1 Announce Type: new Abstract: We describe the BossouChimpanzee video dataset, a unique long-term visual record of wild chimpanzees at an outdoor laboratory for field experiments in B

BrainTRACE: Tracing Longitudinal, Multimodal, and Volumetric Evidence in Brain MRI Clinical Reasoning

arXiv:2610.06571v1 Announce Type: new Abstract: Brain MRI interpretation is a longitudinal clinical reasoning problem: radiologists compare serial studies, integrate information across MRI sequences,

BRANCH-MoE: Balance-Aware Tree Routing for Large Embedding Models

arXiv:2610.06725v1 Announce Type: new Abstract: Mixture-of-experts (MoE) layers increase model capacity without a proportional increase in per-example computation. However, conventional flat routers c

CASE: Cost-Aware Stopping for Efficient Long-Video Agents

arXiv:2610.05400v1 Announce Type: cross Abstract: Long-video agents can actively gather question-relevant evidence, but they typically leave a central decision implicit: when has the agent seen enough

Causal Lag Structure Discovery in Confounded Time Series via Orthogonalized Adaptive Estimation

arXiv:2610.05618v1 Announce Type: cross Abstract: Finding which variables cause which others in multivariate time series, and at what lags, is central to science and policy, yet existing methods force

CCQ: A Multi-State Child Care Quality Dataset to Support AI for Children's Health Research

arXiv:2610.05863v1 Announce Type: new Abstract: High-quality child care in early life is a critical determinant of children's growth and development. Research on child care quality has been constraine

Certification-Enhanced Generalization Bounds

arXiv:2610.06238v1 Announce Type: new Abstract: We investigate the use of formal methods to provide tight and sound generalization bounds for learning algorithms. By casting the traditional notion of

Certification of Real Images through Calibrated Content Authentication

arXiv:2610.05870v1 Announce Type: new Abstract: Generative models can synthesize high-quality inauthentic multimedia content that is already being misused at scale. We evaluate twenty deepfake detecto

CGDD-Net: Context-Guided Dynamic Detail Modeling for Retinal Vessel Segmentation

arXiv:2610.05078v1 Announce Type: new Abstract: Accurate retinal vessel segmentation requires features that capture vascular geometry while preserving information for fine-scale reconstruction. We pro

CHAOSMINING: Benchmarking Post-Hoc Attribution with Sparse Informative Features in High Dimensions

arXiv:2406.12150v2 Announce Type: replace Abstract: Post-hoc attribution is widely used to identify important model inputs, but evaluating whether these attributions identify truly informative feature

CIPHER-MoE: Balancing Efficiency and Routing Fidelity in Trillion-Scale MoE Training

arXiv:2610.05744v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has been widely adopted in recent large language model (LLM) architectures. However, scaling up MoE in LLM training introduces

Claude Opus 5.5 leads at 63.31 and 4.99 per task. GPT 6 Astra is second at 56.25 and 11.61. Sonnet 5.5 follows at 53.14 and $2.82. At the …

model-releasesnous-research--x

Claude Opus 5.5 leads at 63.31 and 4.99 per task. GPT 6 Astra is second at 56.25 and 11.61. Sonnet 5.5 follows at 53.14 and 2.82. At the other end, DeepSeek V4.1 Flash scores 36.91 at 0.26 and Ling 3.

Clean: Second-order LLM Training at Linear Memory Cost via Nystrom Sketching

arXiv:2610.04204v1 Announce Type: new Abstract: Training large language models (LLMs) entails a fundamental trade-off: memory-efficient optimizers such as Adam discard cross-parameter curvature, where

CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling

arXiv:2610.06829v1 Announce Type: cross Abstract: Open-source web agents are now strong enough to execute realistic browser tasks, but training them with reinforcement learning still depends on weak s

ClimateBench v2.0: Probabilistic Climate Model Benchmarking

arXiv:2610.04558v1 Announce Type: cross Abstract: We present ClimateBench v2, a standardized protocol for evaluating climate models on diagnostics expected to be informative for their skill in project

Closed-form trajectory weight surgery: transferring 4B capabilities into 0.8B without billions of tokens (why middle layers break, and how 4 anchor blocks fixed it)

model-releasesr-localllama

Standard distillation usually means burning weeks of compute and billions of tokens hoping the student model eventually mimics the teacher. We wanted to see what happens if you skip backprop entirely

Closing the Context Gap: Activation Alignment for Tabular In-Context Learning

arXiv:2610.06679v1 Announce Type: new Abstract: Tabular foundation models perform in-context learning (ICL) by conditioning predictions on labeled training examples provided as context. Unlike traditi

Code2Games: Enabling Coding Agents for Gaming World Generation

arXiv:2610.05033v1 Announce Type: new Abstract: Generating a high-quality gaming world from a natural-language game intent requires joint reasoning about scene structure, spatial layout, gameplay obje

CodeForge-MA: Execution-Verified Multi-Agent Learning with Language-Conditioned LoRA for Multilingual Code Generation

arXiv:2610.05481v1 Announce Type: cross Abstract: Large language models for code generation often fail on execution, multilingual coverage, and contamination control, especially under frozen backbone

CoDG-Net: Structure-Guided Style Diffusion and Collaborative Learning to Mitigate Catastrophic Forgetting in Medical Image Domain Generalization

arXiv:2610.05053v1 Announce Type: new Abstract: Domain Generalization (DG) for medical image segmentation is both highly challenging and critically important. However, existing medical DG methods larg

CoHyFuse: Condition-wise Hypergraph Fusion with Global Connectome in Task-fMRI

arXiv:2610.05913v1 Announce Type: new Abstract: Task-fMRI connectomes reveal state-dependent neural reconfigurations, yet conventional methods marginalize these signals by aggregating distinct conditi

ColdDDI: Evaluating Knowledge Utilization in Cold-Start Drug-Drug Interaction Prediction

arXiv:2610.05590v1 Announce Type: new Abstract: Cold-start drug-drug interaction (DDI) prediction tests whether models can identify clinically significant interactions for drugs without training-time

Component-Level Evaluation of Adaptive PINN Training for CFD-Oriented Crystal Growth Simulation

arXiv:2610.05127v1 Announce Type: new Abstract: Physics-informed neural network (PINN) training minimizes a weighted combination of partial differential equation (PDE), boundary-condition, and initial

Constrained Goal-directed Planar Graph Generation with Grammar-based Reinforcement Learning

arXiv:2610.06244v1 Announce Type: new Abstract: Planar graphs are central to applications across science and engineering, yet existing generators provide limited support for goal-directed generation u

Continual Action Quality Assessment via Adaptive Manifold-Aligned Graph Regularization

arXiv:2510.06842v2 Announce Type: replace Abstract: Action Quality Assessment (AQA) quantifies human actions in videos, supporting applications in sports scoring, rehabilitation, and skill evaluation.

Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation

model-releasesarxiv-cs-ro

arXiv:2610.06171v1 Announce Type: new Abstract: Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. Ho

Controllable Road Marking Generation

arXiv:2610.05771v1 Announce Type: new Abstract: Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workf

Correct Verdicts, Flawed Reasoning: Structured Auditing of LLM-based Vulnerability Reasoning

arXiv:2610.06366v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed for automated software vulnerability analysis. Binary classification alone is insufficient; pra

COSMOS: Soft Mechanism Mixtures with Verifiable Routing for Long-Horizon PDE Forecasting

arXiv:2610.04427v1 Announce Type: new Abstract: Neural operators offer an efficient alternative to classical PDE solvers, but most learn a monolithic map per equation family and discretization. Real s

DABACO: A Multi-Camera Dataset and Benchmark for Screen Localization and Pointing Estimation

arXiv:2610.03928v1 Announce Type: new Abstract: Screen localization and pointing estimation are key to low-cost interactive devices. Yet developing and evaluating these algorithms requires realistic d

Day-0 support for EmbeddingGemma 2 in llama.cpp https://huggingface.co/ggml-org/embeddinggemma-2-GGUF

model-releasesgeorgi-gerganov--x

On October 6 2026, Georgi Gerganov ( @ggerganov ) announced **day‑0 support for EmbeddingGemma 2 in llama.cpp** on Hugging Face. The announcement linked to the GGUF‑formatted model weights hosted unde

decision models + local ai = ❤️ tried Laya (421M) on llama.cpp in a little apple-picking benchmark, it's almost as good as Qwen 4B at 12x th…

model-releasesgeorgi-gerganov--x

decision models + local ai = ❤️ tried Laya (421M) on llama.cpp in a little apple-picking benchmark, it's almost as good as Qwen 4B at 12x the speed. Media Decision models in llama.cpp are now availabl

Deep Learning Denoising of Real SWOT Sea Surface Height Observations

arXiv:2610.03739v1 Announce Type: cross Abstract: The SWOT (Surface Water Ocean Topography) mission is currently providing unpreceded high-resolution measurements of Sea Surface Height (SSH), revealin

Deep Learning Reforms Image Matching: A Survey and Outlook

arXiv:2506.04619v2 Announce Type: replace Abstract: Image matching, which establishes correspondences between two images to recover 3D structure and camera geometry, is a cornerstone of computer visio

Deep Prior Learning for Embodied Perception

arXiv:2610.05531v1 Announce Type: new Abstract: Embodied systems need geometric perception that exploits available observations beyond images alone. Recent feed-forward 3D models incorporate geometric

Deepseek Peak/Off-Peak and Ownership

Maybe I'm mistaken, but wasn't one of the big pros of Ollama Cloud inference that it was all hosted by Ollama? If that's the case, why duplicate the Deepseek on-/off- hour premiums? Surely they do not

model-releasesr-ollama

DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts

arXiv:2412.10510v5 Announce Type: replace Abstract: The proliferation of disinformation demands reliable and scalable fact-checking solutions. We present Dynamic Evidence-based FAct-checking with Mult

DelegationBench: Measuring When AI Agents Should Ask Before Acting

arXiv:2610.05532v1 Announce Type: cross Abstract: AI agents that send emails, edit files, and make purchases must decide when to act on their own and when to check with the user first. This decision i

DePICT: Decision-Preserving Interface for Constrained Downstream Tasks

arXiv:2610.03945v1 Announce Type: new Abstract: A constrained optimization problem may involve a parameter in its objective and active constraints, yet the final decision may remain insensitive to sma

Detecting Defects that Matter: An Application-Driven Benchmark for Anomaly Detection in Manufacturing and Retail Logistics (VAND 4.0 Challenge)

arXiv:2610.04392v1 Announce Type: new Abstract: Existing Anomaly Detection benchmarks are saturated and often unrealistic. As part of the VAND 4.0 Challenge, we introduce a hidden-test, application-dr

Direct Intermediate Initialization for Tilted Diffusion Samplers

arXiv:2610.06834v1 Announce Type: cross Abstract: Some diffusion posterior samplers construct Gaussian-tilted intermediate distributions along the reverse process. We observe that these targets can be

Disentangling Task Difficulty from Run-Level Failure in Agent Failure Prediction

arXiv:2610.05572v1 Announce Type: new Abstract: Predicting whether an LLM agent will fail has emerged as a promising direction for supporting intervention during execution. Recent approaches report st

Do More Modalities Always Help? A Geometric Perspective on Missing-Modality Robustness

arXiv:2610.04792v1 Announce Type: cross Abstract: Missing modality remains a longstanding challenge in multimodal learning. Existing methods typically address this issue through modality recovery or a

Do Small Language Models Learn to Negotiate? A Controlled Scaling Study of RL-Trained Sellers

arXiv:2610.06204v1 Announce Type: cross Abstract: LLM agents are starting to own the full customer experience. Soon, LLMs may be selling and buying on behalf of companies and customers respectively. S