Search: “model-releases”

Large-scale Repository Engineering via Agent-Native Reusable Code Primitives

arXiv:2610.09079v1 Announce Type: cross Abstract: Large language models equipped with development environments have moved code generation toward repository-scale construction, yet building complete re

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Last week some of South Korea's biggest banks were hit by a cyberattack. We now know the entire hack may have been done by a single person. He used a combined stack of an open-source AI penetration tool named ARTEX, DeepSeek v4.1-Flash, GLM-5.3, Grok 4.6, and Claude Code (CrowdStrike)

DGX agent

CrowdStrike report: https://www.crowdstrike.com/en-us/blog/unknown-threat-actor-uses-artex-to-target-south-korean-finance/ From: Andrew Curran on 𝕏: https://x.com/AndrewCurran_/status/2108108695876092

model-releasesr-localllama

8 Oct 2026

Latent Watermarks under Generative Editing: A Benchmark and Analysis of Detection Survival

arXiv:2610.09702v1 Announce Type: new Abstract: Ordinary prompt-based editing can cause latent watermark detection to fail without explicitly targeting the watermark. We benchmark eight watermark meth

Learning Cross-Model Activation Alignments with Explicit Many-to-Many Layer Maps

arXiv:2610.09058v1 Announce Type: new Abstract: LLMs are released at a rapid pace, raising a natural question: how do two independently trained models relate, both in which layers correspond and in ho

Learning joint probabilistic weather forecasts from station observations alone

arXiv:2610.09898v1 Announce Type: cross Abstract: Assessing compound weather risks requires forecasts representing dependence between variables. CLARA (Calibrated Advection-Routing Attention) learns j

Learning Situation-Conditioned Thinking Policies for Long-Term LLM Agents

arXiv:2610.09590v1 Announce Type: cross Abstract: Long-running autonomous agents must reuse accumulated reasoning experience without allowing explicit historical memory and LLM context to grow indefin

Learning Transition Kernels of Jump-Diffusion Processes with Conditional Diffusion Models

arXiv:2610.09045v1 Announce Type: cross Abstract: We study the problem of learning transition kernels for time-homogeneous jump-diffusion processes using conditional diffusion models, with the goal of

Learning Unknown Constraints without Unsafe Data via Optimality and Counterfactual Regularization

arXiv:2610.09350v1 Announce Type: cross Abstract: Learning from demonstrations (LfD) provides a framework for inferring unknown constraints from locally optimal, constraint-satisfying expert behavior.

Lifelong small-object navigation in changing object layouts: a benchmark and method

arXiv:2610.10125v1 Announce Type: cross Abstract: Household robots need to continually navigate to different objects in the same environment, many of which are small and portable, such as tools and to

LiG-DETR: Local-in-Global Reassembly in Latent Space for Aerial Object Detection

arXiv:2610.09511v1 Announce Type: new Abstract: Aerial object detection faces substantial scale and density variations. Small objects are easily degraded by downsampling and feature compression, while

LightOn OCR-3 is now available on OpenDocRouter, priced at 0.28 / 1m input and 1.40 / 1m output (it is ~$3.19 / 1k pages on ParseBench). W…

model-releasesjerry-liu--x

LightOn OCR-3 is now available on OpenDocRouter, priced at 0.28 / 1m input and 1.40 / 1m output (it is ~$3.19 / 1k pages on ParseBench). We benchmarked it on ParseBench. It is on the pareto frontier f

Lightweight and Versatile Learned Optimization by Recombination of Gradient History

arXiv:2610.09604v1 Announce Type: new Abstract: This paper presents a lightweight and versatile learned optimizer that dynamically recombines gradient history, represented as averages over disjoint ti

LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets

arXiv:2610.09872v1 Announce Type: cross Abstract: Evaluating agents by outcomes alone can obscure the capabilities that produce them. This problem is especially pronounced in evolving environments, wh

LLM4Impact: Integrating Heterogeneous Information for Scientific Impact Prediction

arXiv:2610.10138v1 Announce Type: new Abstract: Predicting the future impact of a newly published paper is challenging because it must be inferred from heterogeneous evidence available at publication

LoGRA: Scaling LLM Reinforcement Learning with Low-Rank Gradient Sketches

arXiv:2610.06647v2 Announce Type: replace Abstract: Reinforcement learning has greatly advanced the capabilities of large language models, but its memory demands remain a barrier to broader adoption.

LRCC: Generalizing Low-Rank Compression with Conditional Computation

arXiv:2610.08858v1 Announce Type: new Abstract: Low-rank compression reduces the cost of pretrained language models by replacing linear transformations with low-rank factorizations. However, conventio

MAGIC: Learning from Visibility Asymmetry for Unsupervised Stereo Matching

arXiv:2508.10838v3 Announce Type: replace Abstract: Learning disparity in occluded regions remains difficult for unsupervised stereo matching. Photometric supervision lacks valid target-view correspon

MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detection

arXiv:2605.24928v2 Announce Type: replace Abstract: Sonar imaging is the primary modality for underwater target detection, yet small targets remain difficult to detect due to insufficient pixel covera

Manifold-Constrained Hyper-Connections for Parameter-Efficient Finetuning

arXiv:2607.18130v2 Announce Type: replace Abstract: Finetuning methods for foundation models usually change weights, prompts, or hidden states, while leaving the residual topology fixed. We ask whethe

MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models

arXiv:2610.09092v1 Announce Type: new Abstract: State Space Models (SSMs) offer an efficient alternative to Transformers for sequence modeling, yet conditioning pre-trained SSMs for iterative generati

Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

arXiv:2610.10351v1 Announce Type: cross Abstract: Differentiable quantum architecture search (DQAS) is a promising framework for the automated design of quantum circuits, particularly for variational

MeshSIPP: Efficient Lattice Planning in Dynamic Environment

arXiv:2610.09652v1 Announce Type: cross Abstract: Autonomous navigation in dynamic environments requires computing spatiotemporal trajectories that satisfy non-holonomic motion constraints. When the t

Meta published a paper that might end the transformer era. For the last seven years, every major AI, ChatGPT, Claude, Gemini, has been built…

model-releasesyann-lecun--x

Meta published a paper that might end the transformer era. For the last seven years, every major AI, ChatGPT, Claude, Gemini, has been built on the exact same architecture. Transformer. But Transforme

MixedPEFT: Combining Multiple PEFT Methods with Mixed Objectives for Unsupervised Domain Adaptation

arXiv:2606.22272v2 Announce Type: replace Abstract: Applying pre-trained language models to new domains through full fine-tuning is computationally expensive and prone to catastrophic forgetting. To a

Moonworks Lunara: Modeling Artistic Intelligence [R]

model-releasesr-machinelearning

Lunara introduces a novel Diffusion Mixture Transformer architecture with fewer than 10B active parameters for modeling artistic intelligence in image generation. Its CAT training algorithm iterativel

MOTIF: Person-of-Interest Deepfake Detection Beyond 3DMM Coefficients

arXiv:2610.09830v1 Announce Type: new Abstract: Video deepfakes targeting a specific individual, the Person-of-Interest (POI), are the most harmful ones, and, since a public figure is abundantly recor

Multi-Label Topic Assignment via LLM Distillation: A Comparative Analysis of Generative vs. Discriminative Student Models

arXiv:2610.09063v1 Announce Type: cross Abstract: Multi-label topic assignment for user-generated content (UGC) -- including product reviews and buyer-seller conversations -- poses unique scalability

MultiFly: A Real-World Multimodal Aerial Dataset with Annotation-Efficient Label Transfer and Cross-Modal Semantic Consistency

arXiv:2610.10359v1 Announce Type: cross Abstract: We introduce MultiFly, a real-world, low-altitude UAV dataset for semantic perception across RGB, thermal, LiDAR, and radar modalities. MultiFly provi

Multiparameter Uncertainty Mapping in Quantitative Molecular MRI using a Physics-Structured Variational Autoencoder (PS-VAE)

arXiv:2602.03317v2 Announce Type: replace-cross Abstract: Quantitative imaging methods, such as magnetic resonance fingerprinting (MRF), aim to extract interpretable pathology biomarkers by estimating

NeuralBES: A Differentiable, Control-Aware Emulator for Scalable Building Energy Modeling

arXiv:2610.10459v1 Announce Type: new Abstract: Demand-side flexibility i.e. forecasting, shifting, and curtailing residential energy loads, depends on thermal models trusted across millions of hetero

Nobody Truly Agrees on Sentiment: Humans, Bespoke Tools, and LLMs Struggle with Social Media Texts

arXiv:2610.10318v1 Announce Type: new Abstract: Social media is a rich source of real-time public sentiment, but widely used sentiment analysis tools are often applied without understanding their limi

Nvidia’s erroneous paper accepted as ICML’s spotlight [D]

model-releasesr-machinelearning

Here is the story: Nvidia has published this work (with source code available) called dreamDojo which is a world model for robotics based of their prior work Cosmos 2.5 which is cited about 100 times

On the complexity of the single-move labeled token routing problem

arXiv:2610.09084v1 Announce Type: cross Abstract: In neutral-atom quantum computers, atoms are moved to target positions along paths of empty positions, and a target position may be reserved for one s

On the Necessity of Attention-FFN Split in Vision Transformers

arXiv:2610.10303v1 Announce Type: new Abstract: The standard Transformer architecture relies on a rigid pattern that alternates Attention and Feed-Forward Network (FFN) layers. Despite its widespread

One Frame, Full Heartbeat: ECG-Free 4D Cardiac Cine MRI Synthesis via Radial-Decomposed Flow Matching

arXiv:2610.09185v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) captures the cardiac cycle as a four-dimensional (4D) sequence, but standard acquisition requires electroca

One Frame, Full Heartbeat: ECG-Free Cardiac Cine MRI Synthesis via Phase-Conditioned Flow Matching

arXiv:2610.09397v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) analysis relies on multi-frame sequences capturing the full cardiac cycle. However, standard multi-frame ac

Online Resource Allocation with an Endogenous Markov State: Fewer LP Solves Earn More

arXiv:2610.09577v1 Announce Type: new Abstract: We study finite-horizon online resource allocation with i.i.d. requests and an endogenous Markov state on a finite state space: each action affects the

Open sourcing Game Summoner, my prompt to game site

model-releasesr-localllama

tldr: Open sourced my prompt to game suite: https://github.com/ndamiano/ai-agent-test, it's MIT licensed, and this runs well on my 5090 with 64gb ram, but any model that can handle tool calls can mana

OpenViTac: Learning and Benchmarking Visuo-Tactile Policies in a Unified Sim-and-Real Framework

arXiv:2610.10384v1 Announce Type: new Abstract: Tactile feedback provides embodied agents with physical information beyond visual observations, enabling more reliable interaction with the real world.

Oracle-Efficient and Parameter-Free Agnostic Smoothed Online Learning

arXiv:2610.10499v1 Announce Type: new Abstract: Online learning is an attractive framework in many domains because it permits well-defined learning even when data are dependent or chosen adversarially

ORACLE: Optimizer-Relative Alignment for Constrained LEarning

arXiv:2610.09040v1 Announce Type: new Abstract: Constraint handling methods typically intervene before the optimizer acts, by modifying the objective or the gradient. Yet momentum, adaptive scaling, a

ORDERS: An Empirical Study of Norm-Rank Aggregation for Personalized Federated Learning

arXiv:2610.10361v1 Announce Type: new Abstract: Personalized federated learning combines shared representations with client-specific predictors, but the contribution of a server weighting rule can be

Origins of Universal Machine Learning Force-Field Errors in Multicomponent Materials

arXiv:2610.09837v1 Announce Type: cross Abstract: Universal machine learning force-field generalization to multicomponent environments generated by compositional design remains insufficiently assessed

PanoPed: Beyond Bounding Boxes for Sim-to-Real Panoramic Pedestrian Tracking

arXiv:2610.08826v1 Announce Type: new Abstract: Full-sphere panoramic cameras let fixed monitoring systems and mobile robots track people in every direction, but a planar bounding box does not fully d

PatchBench: Measuring Collateral Damage in Activation Patching

arXiv:2610.10276v1 Announce Type: cross Abstract: An LLM safety patch can pass a benchmark while still being a poor repair. This risk is especially acute for jailbreak repairs, where the goal is to co

Perceptually Aligned Evaluation of Style Transfer

arXiv:2610.10003v1 Announce Type: new Abstract: Style transfer lacks a reliable evaluation standard: ground truth is inherently ill-defined, and existing automatic metrics often fail to reflect human

Performance at What Cost? A Sustainability-Aware Performance Index for Cell and Nucleus Instance Segmentation

arXiv:2610.10324v1 Announce Type: new Abstract: Pretrained models for cell and nuclear instance segmentation differ substantially in architecture, pretraining data and objectives, parameter count, inf

PHRBench: A Behavioral Evaluation of Post-Hallucination Reasoning in LLMs

arXiv:2610.10455v1 Announce Type: new Abstract: Hallucinated information can propagate through multi-stage LLM systems and become part of the context for subsequent reasoning. Existing studies of post