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Clifford Sheaf Neural Networks

arXiv:2610.01322v1 Announce Type: new Abstract: We introduce the Clifford Sheaf Neural Network (CSNN), an equivariant sheaf neural network for geometric graphs that places a Clifford algebra on each s

Clock Diffusion: Efficient Semi-Autoregressive Continuous Diffusion Language Models

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arXiv:2610.00894v1 Announce Type: new Abstract: Recent works on continuous diffusion for discrete data have demonstrated performance on par with comparable discrete diffusion models. However, these co

model-releasesarxiv-cs-lg

2 Oct 2026

Closed-Loop Refinement and Execution for Learned Driving Planners

arXiv:2610.00992v1 Announce Type: cross Abstract: Learning-based driving planners are usually trained and evaluated in open loop against logged trajectories. In closed loop, a trajectory with small di

researcharxiv-cs-ro

CLoSeR: Closing the Loop for Long-Context Streaming Reconstruction

arXiv:2610.01927v1 Announce Type: new Abstract: Feedforward foundation models have recently shown remarkable 3D reconstruction capabilities. However, existing models exhibit large tracking drift in lo

Closing the Loop: Practical Training Recipes for Looped Language Models

arXiv:2610.00673v1 Announce Type: cross Abstract: Looped language models increase effective depth by repeatedly applying a shared block of layers, but existing large-scale recipes require multi-stage

Code Owns the Simulation, Jev Owns the Evaluation

arXiv:2610.01834v1 Announce Type: new Abstract: Judgment models such as jev{} return, in a single call and without reasoning text, a probability for each described option. This makes them attractive a

Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software

arXiv:2610.00425v1 Announce Type: cross Abstract: Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software pro

CODesign: Consistency from Data to Trajectory in All-Atom Protein Binder Co-Design

arXiv:2610.01773v1 Announce Type: cross Abstract: The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequenc

local-aiarxiv-cs-ai

CoEvolve: Construct-to-Edit Visual Grounding with Bidirectional State Refinement

arXiv:2610.01710v1 Announce Type: new Abstract: Visual grounding localizes an object described by language with a bounding box. Most multimodal grounding models compress target identification, spatial

Cog-VADU: A Training-Free Cognitive Reasoning Framework for Video Anomaly Detection and Understanding

arXiv:2610.01754v1 Announce Type: cross Abstract: Video Anomaly Detection (VAD) aims to temporally localize abnormal events in videos. Most existing approaches rely on dataset-specific training and cu

local-aiarxiv-cs-ai

ColoACT: Multi-Cue Action Chunking for Smooth Autonomous Colon Navigation on a Self-Propelled Endoscopic Robot

arXiv:2610.01258v1 Announce Type: new Abstract: Autonomous colonoscopic navigation can reduce operator burden and the risk of loop formation or tissue trauma, but remains challenging due to deformable

safetyarxiv-cs-ro

Color Independent Word Segmentation From Transcribed Bangla Passages

arXiv:2610.01191v1 Announce Type: new Abstract: An optical character recognition(OCR) system can scan paper and extract text, making people's jobs easier. While numerous OCR systems are accessible in

Comedic Fool's Gold: Reward Exploits and Countermeasures in Conversational Humor

arXiv:2610.00197v1 Announce Type: new Abstract: We investigate automated rewards for training language models in conversational humor, focusing on reward exploits and countermeasures. Two approaches a

CommunityKV: Efficient Long-Context Decoding via Graph Partitioning

arXiv:2610.00418v1 Announce Type: new Abstract: Scaling Transformers to long contexts is constrained by the quadratic cost of self-attention and the linear growth of key-value cache memory transfer. S

Comparing a gradient boosting algorithm to the GOES FDC for wildfire detection

arXiv:2610.01994v1 Announce Type: new Abstract: Wildfires pose severe risks to human life, ecosystems, and property. This study presents a machine learning approach for wildfire detection from GOES AB

Completion Aware Guidance for World Action Models

arXiv:2610.01559v1 Announce Type: cross Abstract: World Action Models (WAMs) predict visual futures and robot actions, yet they remain susceptible to task-incomplete imagination, where plausible, acti

CompMat-Bench: Benchmarking AI Agents for Computational Materials Science

arXiv:2610.00636v1 Announce Type: new Abstract: Evaluating AI agents on scientific research tasks is constrained by the time and resources required for the underlying experiments or calculations. In c

Compositional Embedding Architecture for Physical Field Prediction in Componentized Aerospace Systems

arXiv:2610.00237v1 Announce Type: cross Abstract: Spacecraft thermal design requires repeated evaluation of how variations in the number and spatial arrangement of heat-generating components and in th

local-aiarxiv-cs-lg

Concept Driven Domain Adaptation: Finding an Abstract Needle in a Haystack

model-releasesarxiv-cs-cv

arXiv:2610.00973v1 Announce Type: new Abstract: Science teachers frequently search for documentary excerpts not by describing what appears on screen, but by querying the abstract concepts they intend

Conflicting Supervision Moves Commitment, Not Capability: A 12.29{sigma} arrangement effect that is exactly zero under a convention-agnostic score

arXiv:2610.00234v1 Announce Type: new Abstract: 'Train a model on the same problems written under two incompatible conventions, both correct, and ask what the ordering of that data writes into the par

Constant-Memory Recall: Learned Associations in a Fixed Matrix State

arXiv:2610.00232v1 Announce Type: new Abstract: Fixed-size recurrent memory limits storage growth during inference, but successful recall depends on the task and training. We study a small DeltaNet va

Constant-Time Planning for Chaining Collision-free Motion to Manipulation Behaviors

arXiv:2512.00939v3 Announce Type: replace-cross Abstract: Recent progress in contact-rich robotic manipulation has been striking, yet most deployed systems remain confined to simple, scripted routines

Constitutional Value Potentials: reading and steering internal priority margins in language models

arXiv:2606.15420v2 Announce Type: replace-cross Abstract: Safety evaluations test a policy on prompts that omit the incentive information deployment supplies: a commission, a performance score, a dash

Context-Aware Error Mitigation Orchestration for Hybrid Quantum Reinforcement Learning on NISQ Systems

arXiv:2610.01253v1 Announce Type: new Abstract: Quantum Reinforcement Learning (QRL) integrates reinforcement learning with parameterized quantum circuits and is a promising approach to combinatorial

safetyarxiv-cs-lg

Contextual trajectory and incremental contextual displacement: Towards using LLMs to understand dynamic, utterance-specific meaning construction

arXiv:2610.00840v1 Announce Type: cross Abstract: Transformer-based large language models (LLMs) such as RoBERTa represent text using contextual word embeddings (CWEs), which alter the embeddings asso

Contingent Exposure Routing for Financial AI: Outage Risk and the Cost of Indivisible Decisions

arXiv:2610.00239v1 Announce Type: new Abstract: Model failover restores availability, but changes which financial institutions share decision errors. We formulate outage-contingent routing through a l

agentsarxiv-cs-lg

Continual Concept Erasure in Diffusion Models by Suppressing Cross-Edit Interference

arXiv:2610.01989v1 Announce Type: new Abstract: Concept erasure removes copyright-protected, privacy-sensitive, or otherwise undesirable concepts from pretrained text-to-image diffusion models to supp

Applications

Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations

arXiv:2610.01301v1 Announce Type: cross Abstract: Most current grasp synthesis systems are trained offline and remain fixed during deployment. While this works well when deployment conditions resemble

applicationsarxiv-cs-lg

Continual Reinforcement Learning with Neuroevolution

arXiv:2610.01583v1 Announce Type: cross Abstract: Despite many studies about causes and remedies of plasticity loss in Reinforcement Learning (RL) under continual task changes, no RL method has yet co

Continue, Abort, or Fall: Viability-Aware Policy Selection (VAPS) for Safe Humanoid Acrobatics

arXiv:2610.01397v1 Announce Type: new Abstract: Dynamic humanoid motions such as flips risk hardware damage due to suboptimal policies, disturbances or sim-to-real gaps. A motion tracking policy offer

safetyarxiv-cs-ro

Continuous Conditioning of VLAs with Augmenting EMG and Visual Task Descriptors

arXiv:2610.01794v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models rely strongly on language for describing task information, despite having multimodal inputs. We hypothesize that oth

Continuous Process-Level Evaluation for Evolving Enterprise AI Agent Skills

arXiv:2610.01833v1 Announce Type: new Abstract: Enterprise AI agent skills evolve as tool APIs, models, and specifications change, yet final-output evaluation can miss process-level behavioral drift.

ContractRL: Shielded Group-Relative Policy Optimization for Auditable Tool-Call Repair

arXiv:2610.00328v1 Announce Type: new Abstract: Structured tool calls often fail after only a small number of fields violate a schema or an execution contract. Regenerating the complete object enlarge

Contrastive Attention Mitigates Spectral Bias in Spiking Transformers

arXiv:2610.01403v1 Announce Type: new Abstract: Spiking Transformers merge the energy-efficiency of spiking neural networks (SNNs) with the representational power of self-attention, creating a promisi

Controllable Multi-label Video Safety Detection via Adaptive Tversky Policy Optimization

arXiv:2610.02019v1 Announce Type: cross Abstract: The rapid growth of video-based social media has increased users' exposure to harmful content, creating a need for reliable automated video safety det

safetyarxiv-cs-cv

Convergence Analysis of STORM Under Different Geometries

arXiv:2610.01599v1 Announce Type: cross Abstract: Stochastic recursive momentum (STORM) achieves fast convergence for nonconvex optimization via the variance reduction effect, but existing analyses re

Cool eval. Simply ask an LLM “Land or Water?” and give it a latitude and longitude coordinate as text. Ask 16,200 times, plot as image. The …

Cool eval. Simply ask an LLM “Land or Water?” and give it a latitude and longitude coordinate as text. Ask 16,200 times, plot as image. The models know. From compressing the internet. results for all

researchkarpathy--x

CortexBridge: Cortical Alignment of EEG Montages for Foundation Models

arXiv:2610.01124v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models are often pretrained with a fixed channel vocabulary or a limited set of montages, making transfer diffic

Cost-augmented Schrodinger bridges on graphs are exactly solvable: a Feynman-Kac tilt replaces learned control

arXiv:2610.02195v1 Announce Type: new Abstract: The generalized Schrodinger bridge on a graph moves mass between two distributions while charging a cost for the states visited. It has been approached

Counterfactual Auditing of Bias in Open-Source Large Language Models for Clinical Triage

arXiv:2610.01963v1 Announce Type: new Abstract: Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly

local-aiarxiv-cs-ai

Counterfactual Generation via Flow Matching: Coupling-Sensitive End-to-End Rates

arXiv:2610.01193v1 Announce Type: cross Abstract: Counterfactual generation seeks to sample outcomes under a hypothetical intervention or decision using observational data collected under the factual

Counting Moves, Weighing Voices: Bayesian Dialectical Argumentation for Calibrated Multi-LLM Councils under Persistent Adversaries

arXiv:2610.02005v1 Announce Type: new Abstract: A multi-LLM council lets several large language models (LLMs) deliberate on a question and return an answer together with a confidence estimate. As thes

Coupling Perception and Reasoning in Federated Multimodal Graph Foundation Models

arXiv:2610.00277v1 Announce Type: new Abstract: Federated multimodal graph foundation models (GFMs) aim to adapt pretrained multimodal models to decentralized graph data, where each client owns a priv

Cross-Benchmark Transfer from RL on Agentic Coding Tasks

arXiv:2610.00890v1 Announce Type: cross Abstract: Coding agents often fail in the last mile: they build most of a feature but drop a requirement, test only the cases their implementation already handl

Cross-entropy optimization with prioritized constraints

arXiv:2610.01319v1 Announce Type: new Abstract: When constraints conflict, an optimizer must determine which requirements to preserve and which to relax. On the one hand, a priority ordering specifies

researcharxiv-cs-ro

Cross-Lingual Alignment for Decoder-Only Models using MoE Routers

arXiv:2610.01921v1 Announce Type: cross Abstract: Cross-lingual contrastive learning has been a core component of multilingual encoder training, but the ability to explicitly align representations is

CrossGMN: Graph Metanetworks for Cross-Architecture Weight-Space Transformations

arXiv:2610.01649v1 Announce Type: new Abstract: Weight-space networks operate directly on parameters of other neural networks, enabling tasks such as predicting model properties, editing trained model

Crossing the Cyber Divide: Sim-to-Sim and Sim-to-Real Transfer for RL Agents

arXiv:2610.00759v1 Announce Type: cross Abstract: Cyber attack agents are typically trained and evaluated within a single simulator, making it unclear whether learned policies transfer beyond the envi

safetyarxiv-cs-lg