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Replay-Gated Neural Execution: Decoupling Persistent Behavioral Specifications from Neural Realizations in Frozen Language Models

arXiv:2609.22243v1 Announce Type: new Abstract: Input-conditioned neural interventions raise a runtime question: what persists when one behavioral specification admits multiple actions whose validity

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Human DGX agent

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Model Releases

Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agents

DGX agent

arXiv:2601.15322v3 Announce Type: replace-cross Abstract: Tool-using agents can repeat a final decision while changing their recorded execution. We introduce the Determinism-Faithfulness Assurance Har

model-releasesarxiv-cs-cl

22 Sept 2026

Replicating the Geometry of Emotion Representations in a Base Open-Weights Model

arXiv:2609.22208v1 Announce Type: new Abstract: Sofroniew et al. (2026) report that emotion concepts in Claude Sonnet 4.5 are represented as vectors whose geometry mirrors human affect psychology. We

Replication Without Persistence in Hosted LLMs: Measurement Sensitivity in Action-Time Belief Evaluation

arXiv:2609.22478v1 Announce Type: cross Abstract: Behavioural evaluations of hosted language models can vary because the evaluated service, the measurement instrument, or both differ across runs. We s

Representation-guided in-context learning for medical image interpretation with multimodal large language models

arXiv:2609.24057v1 Announce Type: cross Abstract: Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires re

Residual Primitive Fitting of 3D Shapes with SuperFrusta

arXiv:2512.09201v2 Announce Type: replace-cross Abstract: We introduce a framework for converting 3D shapes into compact and editable assemblies of analytic primitives, directly addressing the persist

RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent

arXiv:2502.07977v3 Announce Type: replace Abstract: Empirical risk minimization (ERM) is a cornerstone of modern machine learning. This paper focuses on the man-in-the-middle (MITM) attack, wherein ad

Resist, Update, Reject: Preference Optimization Installs a Prior-Dependent Reliability Switch

arXiv:2609.22359v1 Announce Type: new Abstract: An aligned model asked to hold its answer against a manipulative source must still update on a reliable one and reject an unreliable one: resistance, re

Resolution-Flexible Decoding for Hybrid Neural Video Representations

arXiv:2609.23555v1 Announce Type: cross Abstract: Neural video representations (NVRs) represent videos using neural network parameters and, in hybrid formulations, frame-wise latent embeddings. Althou

ReSTI: A Source-Grounded Audit and Repair of STI-Bench

arXiv:2609.24727v1 Announce Type: new Abstract: Spatial--temporal benchmarks are valid only when their questions, source annotations, and answer options identify the same physical quantity. We audit S

safetyarxiv-cs-cv

Rethinking Class Imbalance for Single-Cell Foundation Models: A Systematic Benchmark Across Architectures and Long-Tail Loss Functions

arXiv:2609.23325v1 Announce Type: new Abstract: Single-cell foundation models (scGPT, scBERT, Geneformer) achieve cell-type classification accuracy up to 97.5% in our experiments, yet this aggregate a

Rethinking Diffusion Segmentation: When Does It Rely on Its Noisy State, and Does Diffusion Matter?

arXiv:2609.23967v1 Announce Type: new Abstract: Diffusion models are increasingly adapted from generation to conditional prediction, where a conditioning signal is combined with an evolving noisy repr

Rethinking Pivot Programming Languages in Code Language Models

arXiv:2609.22988v1 Announce Type: new Abstract: Multilingual code language models transfer skills across programming languages (PLs), but whether any PL occupies a privileged pivot position remains co

safetyarxiv-cs-cl

Rethinking Streaming Video Diffusion Model: Context, Execution, and Training

arXiv:2609.22283v1 Announce Type: new Abstract: Understanding the design space of streaming video diffusion is essential to exploring its potential for generation quality and computational efficiency.

Rethinking Vision Architectures with Gated Linear Attention and KAN

arXiv:2609.22506v1 Announce Type: new Abstract: Vision Transformers allocate most parameters to multi-layer perceptrons (MLPs) for channel mixing, while token interactions usually rely on quadratic mu

Retrieval Geometry Shapes Cache-Based Clip Adaptation

arXiv:2609.23409v1 Announce Type: new Abstract: Cache-based test-time adaptation improves CLIP predictions by storing and retrieving examples from the target stream while keeping the model frozen. How

ReVeal: A Reconstruction-Aware Real-to-Sim Framework for VLA Policy Evaluation

arXiv:2609.23910v1 Announce Type: new Abstract: Simulation-based evaluation provides a scalable and repeatable alternative to real-world evaluation of vision-language-action (VLA) policies. However, r

Revisiting Multi-View Stereo: A Sequence-to-Sequence Formulation

arXiv:2609.24850v1 Announce Type: new Abstract: Computing accurate geometry from multi-view images is a fundamental problem in computer vision. Recent feed-forward (FF) models jointly estimate 3D geom

RewardVerse: Rubric-Guided Policy Optimization for Video Reward Modeling

arXiv:2609.22947v1 Announce Type: new Abstract: Reinforcement learning (RL) is vital for optimizing video generation models, with a robust reward model (RM) serving as the cornerstone. However, existi

RheOFormer: A generative transformer model for simulation of complex fluids and flows

arXiv:2510.01365v2 Announce Type: replace Abstract: The ability to model mechanics of soft materials under flowing conditions is key in designing and engineering processes and materials with targeted

Riemannian Density-Driven Optimal Control: Tangent-Space LQR for Second-Order Multi-Agent Systems on Curved Manifolds

arXiv:2609.22678v1 Announce Type: cross Abstract: Density-Driven Optimal Control (D2OC) provides an effective framework for steering multi-agent systems toward prescribed spatial distributions. Howeve

Local Ai

Risk-Aware Motion Planning and Control under Unknown Dynamics with Hybrid Observations

arXiv:2609.23792v1 Announce Type: new Abstract: We consider robotic motion planning and control under unknown dynamics with hybrid state observations, where state measurements are available only in pa

local-aiarxiv-cs-ro

RiverVLN: Phase-Grounded Temporal Vision--Language Navigation for Unmanned Surface Vehicles

model-releasesarxiv-cs-ro

arXiv:2609.23423v1 Announce Type: new Abstract: Vision-language navigation (VLN) has largely been developed for indoor and terrestrial robots, where language can often be treated as a static goal and

RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner

arXiv:2410.23912v3 Announce Type: replace-cross Abstract: The reasoning abilities of large language models (LLMs) have improved with chain-of-thought (CoT) prompting, allowing models to solve complex

RLVR is a Kernel, Not a Function: Statistical Inference for pass@k Crossovers

arXiv:2609.22547v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) often improves pass@1 while falling behind its base model at larger sampling budgets k, a crosso

researcharxiv-cs-lg

RLVR^{2}: Reinforcement Learning with Verifiable Rubric-based Ranking

arXiv:2609.23457v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is expanding from tasks with well-defined correctness signals, such as mathematics and code, towar

Tutorials

Robot Programming with Augmented Reality: The Role of Spatial Ability

arXiv:2602.03544v2 Announce Type: replace Abstract: Programming a robot arm requires users to interpret coordinate frames, joint rotations, and trajectories that are not directly visible. Augmented re

tutorialsarxiv-cs-ro

Robot World Models Are Not Invariant to How the Actions Are Written

arXiv:2609.23252v1 Announce Type: cross Abstract: A robot policy is trained with one of two action parameterizations: absolute joint targets, or deltas relative to the current state. The choice is a l

Local Ai

RoboTalk: Learning Multi-Robot Communication and Coordination from Multimodal Demonstrations

arXiv:2609.23997v1 Announce Type: new Abstract: Multi-robot collaboration could enable more efficient and scalable solutions to complex robotic tasks, but collaboration under partial observability rem

local-aiarxiv-cs-ro

Robotic Valve Turning: Axial Misalignment Correction Using Reaction Torque Feedback

arXiv:2609.24413v1 Announce Type: new Abstract: In this work, we propose a haptic update control law that uses reaction torques to correct axial misalignment during robotic valve manipulation. Unlike

researcharxiv-cs-ro

Robust Market Making with Hawkes Order Flow and Price Impact via Adversarial Reinforcement Learning

arXiv:2609.22785v1 Announce Type: new Abstract: Market-making strategies in real limit order book markets face substantial model uncertainty and regime-shift risk. Existing adversarial reinforcement l

Role-Aware Morgan Fingerprints for Reaction Yield Prediction

arXiv:2609.22167v1 Announce Type: new Abstract: Predicting reaction yield from molecular structure and reaction context can cut experimental trial-and-error and speed up condition screening in synthet

researcharxiv-cs-lg

RopeFormer: Cross-Trial Adaptation from Interaction History for Dynamic Rope Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.23432v1 Announce Type: new Abstract: Dynamic rope manipulation is highly sensitive to unknown object dynamics: the same robot motion can produce substantially different responses across rop

Rough Stochastic Pontryagin Maximum Principle and an Indirect Shooting Method

arXiv:2502.06726v4 Announce Type: replace-cross Abstract: We derive first-order Pontryagin optimality conditions for stochastic optimal control with deterministic controls for systems modeled by rough

researcharxiv-cs-ro

RPMem: Learning Long-Term Recurrent Parametric Memory Across Sessions for LLM Agents

arXiv:2609.23466v1 Announce Type: new Abstract: Long-running LLM agents require memory that persists and evolves across sessions. Text-based memory retrieves and reconstructs past interactions at ever

researcharxiv-cs-cl

RRSI: Regularized Recursive Self-Improvement of Agent Harnesses

arXiv:2609.24972v1 Announce Type: cross Abstract: An LLM agent's capability is largely magnified by its harness, namely the prompts, control flow, tooling, memory, and context management surrounding t

RS-Claw-Evolution: Environment-Feedback-Driven Evolution for Lightweight Remote Sensing Agents in Long-Horizon Tasks

arXiv:2609.22258v1 Announce Type: cross Abstract: Large language model-driven remote sensing (RS) agents offer a promising approach to automating geospatial analysis. However, lightweight RS agents ba

RSPDBench: Benchmarking Vision Foundation Models on Earth Observation Tasks Under Physically Grounded Remote-Sensing Product Degradations

arXiv:2609.23427v1 Announce Type: new Abstract: Vision foundation models targeting Earth observation (EO) tasks are commonly evaluated on clean downstream benchmarks, but operational EO products can a

safetyarxiv-cs-cv

Rule-Constrained Assignment for Cue-Ball Identification in Broadcast Snooker

arXiv:2609.23450v1 Announce Type: new Abstract: Accurate cue-ball identification is essential for metric analysis of broadcast snooker. Existing systems evaluate each candidate independently against a

Safe Learning for Contact-Rich Robot Tasks: A Survey from Classical Learning-Based Methods to Safe Foundation Models

arXiv:2512.11908v3 Announce Type: replace Abstract: Contact-rich tasks pose significant challenges for robotic systems due to inherent uncertainty, complex dynamics, and the high risk of damage during

SAFe: Segment-guided Aggregation of Feature Densities for Anomaly-aware Segmentation

arXiv:2609.24204v1 Announce Type: new Abstract: Visual segmentation systems encounter objects outside their training distribution during real-world deployment, hindering reliable autonomous systems th

SafeTune: A Unified Faithful Library for Auditing and Repairing Safety Drift in Fine-Tuned LLMs

arXiv:2609.22153v1 Announce Type: new Abstract: Methods for addressing safety drift in fine-tuned Large Language Models (LLMs) are scattered across incompatible implementations, lifecycle stages, and

Safety Control of a Hyper-redundant Robot via Adaptive Weighted Control Barrier Functions

arXiv:2609.24062v1 Announce Type: new Abstract: Hyper-redundant robots are well suited for confined-space manipulation due to their high dexterity, but safe operation in cluttered environments remains

Safety-Critical Control under Uncertainty via Adaptive Conformal Quantile Prediction Intervals

arXiv:2609.23280v1 Announce Type: new Abstract: Safety-critical control under uncertainty requires uncertainty representations that are both statistically valid (for certifiable performance) and compa

Local Ai

SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773v1 Announce Type: cross Abstract: Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under un

local-aiarxiv-cs-lg

Applications

SAIL: Test-Time Scaling for In-Context Imitation Learning with VLM

arXiv:2603.08269v2 Announce Type: replace Abstract: In-context imitation learning allows robots to acquire skills from demonstrations, yet one-shot trajectory generation remains fragile under environm

applicationsarxiv-cs-ro

SalQ-VLM: Fine-Grained Saliency-Guided Quantization for Vision-Language Models

arXiv:2508.03351v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities across diverse language tasks, motivating their extension to vision-lan

Agents

SALSA: Semi-Autonomous Literature Summarization Assistant

arXiv:2609.22210v1 Announce Type: new Abstract: SALSA (Semi-Autonomous Literature Summarization Assistant) is an open- source, human-in-the-loop platform for extracting structured scientific datasets

agentsarxiv-cs-cl