Search: “model-releases”

ReMAP: Lossless Residual Neural Lifting for Scalable MAP Inference in Arbitrary-Order Markov Random Fields

arXiv:2411.18954v5 Announce Type: replace Abstract: Maximum a posteriori inference in a finite Markov random field is generally NP-hard. We study an instance-wise optimizer that minimizes the exact mu

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Model Releases

Remember alphaXiv? Their new research agents are told to report on users without telling them with no disclosure [D]

DGX agent

I was curious about OpenResearch by alphaXiv. 'Turn your coding agents into research agents'? Sounds great! Just what I needed to save time on my experiments. So I copy pasted their repo into Claude a

model-releasesr-machinelearning

14 Oct 2026

Remembering What Matters for Long-Horizon Robotic World Models

arXiv:2610.14583v1 Announce Type: cross Abstract: Autoregressive robot video world models based on discrete visual tokens remain unreliable over long rollout horizons. Retaining the entire generated h

RepProbe: Can Video Language Models Count Repeated Actions? A Diagnostic Benchmark

arXiv:2610.18844v1 Announce Type: new Abstract: Repetition counting requires identifying and enumerating action cycles over time. While state-of-the-art video language models describe actions fluently

Representation Drift in Continual Learning: LoRA versus N-gram Memory

arXiv:2610.14921v1 Announce Type: new Abstract: A language model that keeps learning online must not slowly erode its own base capabilities. We ask which part of a modern LLM should absorb continual u

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

arXiv:2610.14474v1 Announce Type: new Abstract: Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-m

ReTerm: Recovery Training for Self-Improving Terminal Agents

arXiv:2610.18484v1 Announce Type: cross Abstract: Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective

arXiv:2510.05023v2 Announce Type: replace Abstract: Langevin-based Thompson Sampling (TS) methods for multi-armed bandits use likelihood gradients to approximate posterior samples when exact sampling

Rethinking LLM-Guided Visual Question Answering: Does Deeper Knowledge Integration Really Help?

arXiv:2610.17079v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering (VQA) requires reasoning that extends beyond visible image content, demanding external commonsense and factual

Rethinking Supervision in Document Unwarping: A Self-consistent Flow-free Approach

arXiv:2610.15445v1 Announce Type: new Abstract: In recent years, the proliferation of smartphones has led to an upsurge in the digitization of document files via these portable devices. However, image

ReTrace: Cross-Stage Failure Attribution for Self-Improving Robotic Manipulation

arXiv:2610.15814v1 Announce Type: new Abstract: General-purpose multimodal foundation models are increasingly capable of directly controlling robots, yet improving their manipulation capabilities thro

Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift

arXiv:2606.15734v2 Announce Type: replace-cross Abstract: Continual post-training enables models to absorb emerging knowledge after deployment, but repeatedly updating shared parameters can accumulate

Revisiting the 16x Pretraining Compute Gap between Diffusion and Autoregressive Language Models

arXiv:2610.17590v1 Announce Type: new Abstract: Diffusion language models (DLMs) have attracted wide attention for their fast, parallel decoding, but they are believed to be far less efficient to trai

Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning

arXiv:2511.00655v3 Announce Type: replace Abstract: Federated learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its scalability is limited by

RIECNN: Real-Time Image Enhanced CNN for Traffic Sign Recognition

arXiv:2610.15127v1 Announce Type: new Abstract: Traffic sign recognition plays a crucial role in the development of autonomous cars to reduce the accident rate and promote road safety. It has been a n

RIFT: Token Influence Follows the Path of Least Resistance

arXiv:2610.16349v1 Announce Type: cross Abstract: Which context tokens drive a language model's answer? Graph-based tools such as attention rollout and attention flow answer this from a single forward

RoboBugBench: Benchmarking Automated Repair of Real Robot Software Under an Audited Behavioral Oracle

arXiv:2610.16369v1 Announce Type: new Abstract: Language agents increasingly modify robot software, but whether they can repair it is unmeasured, because the domain supplies no oracle to inherit: a ro

RoboHarness: A Simple Harness Outperforms VLA and World Actions Models

arXiv:2610.14018v1 Announce Type: new Abstract: The rise of large language models (LLMs) has opened a path toward generalist embodied AI, raising the question of how LLMs can act in the physical world

Robust Logical Anomaly Detection under Capture Shifts via Synthetic Anomalies

arXiv:2610.18295v1 Announce Type: new Abstract: Detectors of logical anomalies, such as missing, extra or wrongly combined parts, usually score a test image by its distance from normal (good) images.

Robustly Reliable Learning for Regression

arXiv:2610.17381v1 Announce Type: new Abstract: We introduce the problem of robustly reliable learning for the regression setting in adversarial environments. Given a test point x_{test}, a training d

RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM

arXiv:2610.15157v1 Announce Type: cross Abstract: Efficient perception is a prerequisite for the small, low-power devices targeted by robotics, mixed reality, autonomous driving, and drone application

RSIgen: Reciprocal Self-Improvement for Agentic Visual Generation

arXiv:2610.18688v1 Announce Type: new Abstract: Agentic visual generation produces experience that can improve the native understanding (agent) and generation roles of a unified multimodal backbone, b

RT-J: Large-Scale Pretraining of Relational Transformers for Context-Efficient Predictions

arXiv:2610.17867v1 Announce Type: new Abstract: Foundation models for tables and relational databases are increasingly used for predictive tasks across various scientific and industrial domains. Howev

Sabi-Noema: A capability and efficiency focused fine-tune of Qwen 3.8 27B

model-releasesr-localllama

tl;dr: new qwen finetune that simultaneously pushes the frontiers of small model capability and reasoning efficiency. Hey everyone, We publish two post-trained versions of Qwen 3.8 27B called Sabi-Noe

Same Function, Different Trajectory: No Standard Optimizer Is Equivariant to Transformer Reparameterization

arXiv:2610.18085v1 Announce Type: new Abstract: We show that two Transformers representing the same function can follow different training trajectories. For example, doubling a query matrix and halvin

Sampling from Neural Operator Priors to Solve Partial Differential Equations

arXiv:2610.16396v1 Announce Type: new Abstract: Guided sampling with sparse observations and PDE residuals has recently been combined with neural operator priors to solve partial differential equation

Sanzaru: Benchmarking Protocol Formation under Epistemic & Communication Asymmetry

arXiv:2610.15163v1 Announce Type: cross Abstract: A language model's ability to solve a task individually does not ensure that a team can solve it under unequal access to information and communication

SarcasTraps: Effect of Sarcasm on Turkish Hate Speech Detection

arXiv:2610.16957v1 Announce Type: cross Abstract: Standard hate speech detection datasets often emphasize explicit harmful language, but directed harm can also be expressed indirectly, without clearly

Scalable Identification of Physics-Based and Neural Dynamics from Partial Measurements

arXiv:2610.16559v1 Announce Type: cross Abstract: We present a scalable method for identifying nonlinear dynamics from partial measurements, supporting physics-based, neural-network, and gray-box mode

Scaling code generation without scaling review risks turning coding gains into a larger “review” backlog (whether during PR review or later,…

model-releasesitamar-friedman--x

Scaling code generation without scaling review risks turning coding gains into a larger “review” backlog (whether during PR review or later, when dealing with technical debt, incidents, or bugs). The

SceneForesee: Learning Scene Evolution for Spatiotemporal Reasoning

arXiv:2610.14439v1 Announce Type: new Abstract: Large multimodal models (LMMs) need to understand how entities move and interact as a scene develops. This requires following the same entities over tim

ScenePercept: Scenario-Conditioned Perceptual Assessment of Real-World User-Generated Content Images

arXiv:2610.17661v1 Announce Type: new Abstract: The rapid development of mobile imaging and social platforms has led to explosive growth in user-generated content images, making their systematic and c

scHFBiMamba: a bidirectional Mamba autoencoder for cardiac disease-state classification from single-nucleus RNA-seq data

arXiv:2610.15117v1 Announce Type: new Abstract: To evaluate whether a compact bidirectional state-space autoencoder improves joint classification of species, cell type, and disease state from single-n

SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference

arXiv:2610.17146v1 Announce Type: cross Abstract: Bayesian predictive regions account for parameter uncertainty but can be poorly calibrated under model misspecification, even with expensive full MCMC

SEAR: Self-Evolving Agentic Robotics

arXiv:2610.18792v1 Announce Type: new Abstract: Frontier language-model agents can now improve robots on their own: they write control code, test it, and keep what works as skills and memories for the

Searching for What Matters: Open-Ended Discovery of Multiple Hypotheses with Agentic Data Exploration

arXiv:2610.17874v1 Announce Type: new Abstract: Discovering what drives an outcome from data is central to science and often requires deciding what is worth investigating before a specific hypothesis

Self-Creating Random Walks for Decentralized Learning under Pac-Man Attacks

arXiv:2601.07674v3 Announce Type: replace-cross Abstract: Random walk (RW)-based algorithms have long been popular in distributed systems due to low overheads and scalability, with recent growing appl

Self-Verifier Capture in Unified Visual Generators: Diagnosing and Repairing Closed-Loop Self-Reward

arXiv:2610.16500v1 Announce Type: new Abstract: Image-space reward requires decoding and a separate judge; unified visual generators can instead reuse their understanding pathway for decode-free, self

SenseWeather: Multimodal Sensing for Robust Robotic Perception under Extreme Conditions

arXiv:2610.14082v1 Announce Type: cross Abstract: Robotic perception must remain reliable when extreme environmental conditions severely degrade the primary RGB observation. Although robotic platforms

Sensitivity Fidelity Reveals Physical Dependencies Beyond Forecast Accuracy in Deep-Learning Earth-System Models

arXiv:2610.15540v1 Announce Type: new Abstract: Deep-learning models increasingly rival numerical simulation in Earth-system forecasting, yet forecast error alone cannot determine whether their learne

Sensitivity or Criterion? Measuring and Moving When Language Models Act

arXiv:2610.15415v1 Announce Type: cross Abstract: Before an agent acts, it must decide whether action is warranted. A single accuracy cannot distinguish failure to recognize a warranted action from re

Separating Prompt Harmfulness from Interaction Safety via Partial Generation

arXiv:2610.16761v1 Announce Type: cross Abstract: LLM-based information systems need safety guardrails. Most guardrails classify the prompt alone. If the prompt looks harmful, the system rejects it be

Sequence-Structured Decision Learning for Branch-and-Bound in Mixed-Integer Linear Programming

arXiv:2610.14835v1 Announce Type: new Abstract: Branch-and-bound (BnB) solves mixed-integer linear programs by constructing and exploring a search tree. Node selection and branching are two recurrent

SERF: Spatiotemporal Environment and Robot Feature Map for Long-Horizon Mobile Manipulation

arXiv:2606.12956v2 Announce Type: replace Abstract: Long-horizon robot mobile manipulation requires continual reasoning about localization, environment changes, and task progress, all of which are cha

Shaping Latent Mixture-of-Experts: From Expert Geometry to Layerwise Capacity Allocation

arXiv:2610.14644v1 Announce Type: cross Abstract: Fine-grained mixture-of-experts (MoE) models commonly increase expert count by narrowing each expert, treating expert shape as a by-product of routing

ShellElastic: Scalable Elastic Pretraining with Simultaneous Maximal Updates and Hyperparameter Transfer

arXiv:2610.15124v1 Announce Type: new Abstract: Foundation models need to support diverse inference budgets, yet training a separate model for each budget duplicates pretraining effort. Elastic models

ShoeFit: A New Dataset and Dual-image-stream DiT Framework for Virtual Footwear Try-On

arXiv:2610.18325v1 Announce Type: new Abstract: Virtual footwear try-on (VFTON), a critical yet underexplored area in virtual try-on (VTON), aims to synthesize faithful try-on results given diverse fo

SidewalkBench: Benchmarking Visual Navigation on Urban Sidewalks

arXiv:2606.16953v2 Announce Type: replace Abstract: Urban sidewalk navigation presents significant challenges due to complex structural layouts, dynamic pedestrian behaviors, and long distances. While