All entries

CMP-IRRT*: A Perception-Assisted Height-Adaptive Planner for Quadruped Robots

arXiv:2610.10470v1 Announce Type: new Abstract: Quadruped robots can traverse low obstacles, but many 2D planning pipelines still model obstacles as binary occupied regions and rely on sampling-based

safetyarxiv-cs-ro

Co-Evolving Robot Orchestrators and Policies through Deployment

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

arXiv:2610.09228v1 Announce Type: new Abstract: Vision-language-action (VLA) policies trained on large datasets are capable within their training domains, yet they still fail to generalize to the vari

safetyarxiv-cs-ro

8 Oct 2026

Co{}^{2}Skill: Whole-Body Control via Skill Composition for Long-Horizon Human-Environment Interaction

arXiv:2610.09291v1 Announce Type: new Abstract: Achieving human-level dexterity in complex, unstructured environments requires the seamless integration of whole-body scene interaction and dexterous ob

safetyarxiv-cs-ro

Coding-Agent Benchmarks Should Match Their Users' Task Flows

model-releasesarxiv-cs-cl

arXiv:2610.09633v1 Announce Type: cross Abstract: The evaluation of coding agents generally strives to be as realistic as possible. In our study, we collect 4,782 agent sessions of real software engin

CoDR: Training-Free Confidence-Drift Remasking for Diffusion Language Models

arXiv:2610.08833v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) decode by repeatedly committing tokens to masked positions, but these commitments are usually irreversible. A t

researcharxiv-cs-cl

Collaborative Reasoning Distillation via Cross-Feedback and Coherent Curation

arXiv:2610.09587v1 Announce Type: cross Abstract: Reasoning capabilities are critical for advancing Large Language Models, yet current approaches either require massive computational budgets or strugg

researcharxiv-cs-cl

Collective Behavior of AI Agents: the Case of Moltbook

arXiv:2602.09270v2 Announce Type: replace-cross Abstract: We present a large scale data analysis of Moltbook, a Reddit-style social media platform exclusively populated by AI agents. Analyzing over 4

researcharxiv-cs-cl

Hardware

come hear about building with open frontier models Open Haus Berlin lineup: → @RiqwanMThamir from @n8n_io → Harry Kim from @nvidia → @zainha…

come hear about building with open frontier models Open Haus Berlin lineup: → @RiqwanMThamir from @n8n_io → Harry Kim from @nvidia → @zainhas from Together AI good food, drinks, and better arguments a

hardwaretogether-ai--x

Comparing Qwen3.8-27B fine-tunes and baselining vs. frontier

model-releasesr-localllama

TL;DR: For my use case, mradermacher/Signal-3.8-27B-Terse-Coder.i1-Q4_K_M proved out. Ymmv based on your domain-specific tests. Time taken to solve problems compared to frontier models is massive; esp

Composing What Each Teacher Learned: Multi-Teacher On-Policy Distillation through Teacher-Relative Shifts

arXiv:2610.10460v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one

Computations of the slice genus and the unknotting number of links via machine learning

arXiv:2610.10206v1 Announce Type: cross Abstract: Links are disjoint unions of circles smoothly embedded in S^3. We use reinforcement learning and Bayesian optimisation to obtain new upper bounds on s

Concentration, Not Uncertainty: Why Targeted Synthetic Data Doesn't Help Camouflaged Object Detection

arXiv:2610.09807v1 Announce Type: new Abstract: Camouflaged object detection requires pixel-accurate masks, but obtaining such annotations is slow and costly, making synthetic training images an attra

researcharxiv-cs-cv

Conditional Accuracy Profiles: Diagnosing LLM Judges across Deployment Conditions

arXiv:2610.09229v1 Announce Type: new Abstract: LLM-as-judge is now a standard tool for scalable evaluation, but judge performance is still often summarized by a single accuracy number. This aggregate

Local Ai

Conditional Flow Matching for Generation of 3D Multi-variable Instantaneous Urban Microclimate Fields

arXiv:2610.10430v1 Announce Type: cross Abstract: Rapid and accurate prediction of urban wind and temperature fields is important for urban microclimate design and climate adaptation. Large-eddy simul

local-aiarxiv-cs-lg

Conformal Prediction for Spatially Dependent Data via Sequential Whitening

arXiv:2610.10168v1 Announce Type: cross Abstract: Split conformal prediction uses prediction errors on held-out (calibration) data to determine how wide the prediction intervals should be. It guarante

Tutorials

Consistent Distribution Matching for Data-Free Diffusion Distillation

arXiv:2610.09221v1 Announce Type: cross Abstract: Flow and diffusion models suffer from slow inference due to computationally expensive numerical integration. Distillation provides a promising way for

tutorialsarxiv-cs-cv

Constitution-Guided Watermarking

arXiv:2610.09552v1 Announce Type: cross Abstract: Watermarking enables language model providers to identify text generated by their models. However, its desired properties can conflict (ie~stronger wa

Constrained-Action AI Remediation for SIEM/XDR via a NeMo-Guardrails Proxy

arXiv:2610.09906v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) for information technology and operational technology share one incident-response problem: a flood of correlated al

Constraint Tree Exploration for Learning from Language Feedback

arXiv:2610.09107v1 Announce Type: cross Abstract: Natural-language feedback in interactive learning often explains why an action failed by pointing to violated requirements. Misinterpreting this feedb

agentsarxiv-cs-cl

Contact-Aware Imitation Learning Through Contact Factorization

arXiv:2610.09533v1 Announce Type: new Abstract: Generalizable contact-rich manipulation requires robots to preserve intended task behavior while adapting its physical realization to changing contact c

safetyarxiv-cs-ro

Context-Aware Adaptive Pesticide Spraying for Agricultural Robots under Changing Weather and Terrain Using Vision-Language Models

arXiv:2610.08807v1 Announce Type: new Abstract: Precision pesticide spraying is essential for optimizing application efficiency and ensuring uniform chemical distribution. Spraying performance is infl

researcharxiv-cs-ro

Context-aware Attention-based Gaussian Mixture Models for Vehicular Trajectory Prediction

arXiv:2610.09174v1 Announce Type: new Abstract: Reliable and interpretable trajectory prediction is critical for cooperative and autonomous driving in complex and uncertain environments. This paper in

agentsarxiv-cs-lg

Continual Graph Multi-Agent Reinforcement Learning

arXiv:2610.10302v1 Announce Type: new Abstract: In Continual Multi-Agent Reinforcement Learning (CMARL), agents learn cooperative policies across sequences of tasks, aiming to adapt effectively to new

Continual Learning without Continual Training

arXiv:2610.10379v1 Announce Type: new Abstract: Continual learning requires models to adapt to new domains and new classes while retaining prior knowledge. Many existing methods rely on continued opti

Controllable Crowd Generation through World-Model Planning

arXiv:2610.09438v1 Announce Type: new Abstract: Crowd simulation plays a central role in robot navigation, autonomous driving, and urban planning. For these applications, realistic simulation requires

agentsarxiv-cs-cv

Controlling Dependence in Implicit Generative Models via Spread Mutual Information

arXiv:2610.10021v1 Announce Type: cross Abstract: Mutual information (MI) provides an objective for suppressing or encouraging statistical dependence in implicit generative models. However, direct MI

Convex-Concave Reinforcement Learning

arXiv:2610.09108v1 Announce Type: new Abstract: Policy learning drives many of the most consequential and heavily-invested applications of reinforcement learning today. Yet the core optimization probl

safetyarxiv-cs-lg

COOL: Curiosity-Driven Object Ownership Learning for Personalized Robotic Assistance

arXiv:2610.09358v1 Announce Type: new Abstract: Robots are increasingly expected to provide personalized services in everyday environments. To do so, they must ground natural-language commands such as

agentsarxiv-cs-ro

COPC: Coupled Off-Policy Correction for Asynchronous LLM Reinforcement Learning

arXiv:2610.09597v1 Announce Type: new Abstract: Asynchronous RL accelerates large language model post-training by decoupling rollout generation from optimization, but trains on stale trajectories. Exi

CoreWeave Forge aims to speed up the AI improvement loop

Enterprises racing to put agents into production are learning that the AI improvement loop never really ends. Agents must be run, observed, evaluated and improved continuously. CoreWeave Inc. has been

agentssiliconangle

Applications

CoreWeave makes the case for an open, full-stack AI cloud

The full-stack AI cloud market is about more than access to graphics processing units: it also encompasses the tools needed to improve models and agents in production. Providers are seeking to disting

applicationssiliconangle

Correspondences as Decisions: JevNexus for Decision-Centric Schema Matching

arXiv:2610.09487v1 Announce Type: cross Abstract: Schema matching increasingly uses generative language models to rerank retrieved column candidates, although the underlying task is a bounded correspo

Cost Agent: find where your LLM and agent spend goes with your traces

AI costs don’t always scale predictably with traffic. A retry loop, oversized context window, or unnecessarily expensive model can make a small number of traces disproportionately expensive. The post

model-releasesarize-ai

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existi

Counterfactual Route Optimization for Gaussian Head Avatar Modeling

arXiv:2610.09791v1 Announce Type: new Abstract: Head avatar modeling requires jointly optimizing multiple objectives with different dominant effects on geometry, appearance, and cross-view consistency

researcharxiv-cs-cv

Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models

arXiv:2610.09070v1 Announce Type: cross Abstract: Multivariate ordinal data along with covariates are commonly collected in problems ranging from alignment of language models with human preferences, a

safetyarxiv-cs-lg

Cross-Domain Pretraining for Steady-State Neural CFD Surrogates

arXiv:2610.10398v1 Announce Type: new Abstract: Neural surrogates for computational fluid dynamics (CFD) have the potential to greatly enhance engineering innovation through accelerating simulation. H

CRT-HMAR: Causal Requirement Tracing-Guided Hierarchical Multi-Agent Regulation for Open-Task-Aware Infrared-Visible Image Fusion

arXiv:2610.09330v1 Announce Type: new Abstract: Infrared and visible (IR-VIS) image fusion integrates complementary multimodal information into a single fused image to support downstream vision tasks.

agentsarxiv-cs-cv

Local Ai

Currently having high success with this little niche finetune i found sitting in the corner of huggingface

Currently having high success with this little niche finetune i found sitting in the corner of huggingface If you want to try it out here is a smaller quantisation iq3_s works really well in my codeba

local-air-localllama

CurveTQ: Rotation-Free Trellis Quantization of LLM Weights via Curvature-Weighted Search

arXiv:2610.09212v1 Announce Type: new Abstract: The best two-bit weight quantizers for large language models, such as QTIP and Proteus, rotate each weight matrix by a random orthogonal transform, whic

Darwinium launches two intent intelligence capabilities to catch fraud by AI agents

model-releasessiliconangle

Fraud prevention startup Darwinium UK Ltd. today launched two new capabilities that make intent intelligence the foundation of its platform. Journey Transition Probability flags unusual changes in the

Data Reuse in Non-Stationary Learning

arXiv:2610.10340v1 Announce Type: cross Abstract: We consider online learning in non-stationary environments, where the goal is to track an unknown parameter that switches abruptly between a finite se

Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

arXiv:2610.10347v1 Announce Type: cross Abstract: Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically

Decentralized SGD under Heavy-Tailed Noise: Optimal Convergence Rates and the Role of Gradient Clipping

arXiv:2610.10527v1 Announce Type: cross Abstract: Heavy-tailed noise has been widely observed in modern machine learning, motivating the use of methods like gradient clipping and normalization. While

Decoding Neural Population Dynamics through Robotic Analog

arXiv:2610.09977v1 Announce Type: new Abstract: Animal evidence shows that precise voluntary movements arise from rotational neural population dynamics in motor cortex, but their physical effects rema

researcharxiv-cs-ro

Decoupled Optimization for Teacher-Student Semi-Supervised Learning via a Pioneer Student

arXiv:2610.09609v1 Announce Type: new Abstract: Semi-supervised learning (SSL) relies on two core mechanisms: self-training under the Teacher-Student (T-S) framework and joint optimization of labeled

Decoupling Exploration from Optimization in RLVR

arXiv:2610.10536v1 Announce Type: cross Abstract: Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints. A key promise of RLVR is t

Decoupling Logic from Persona: Structural Immunity of Edge LLM Agents to Context Pollution

model-releasesarxiv-cs-cl

arXiv:2610.09772v1 Announce Type: new Abstract: Small language-model agents on edge devices must hold a persona and reason correctly at once, inside one context window that fills with conversational h