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ReasoningShield: Safety Detection over Reasoning Traces of Large Reasoning Models

arXiv:2505.17244v3 Announce Type: replace-cross Abstract: Large Reasoning Models (LRMs) leverage explicit reasoning traces, known as Chain-of-Thought (CoT) reasoning, to decompose complex problems int

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Safety

ReAT: Residual Action Tokenization for Autoregressive Robot Policies

DGX agent

arXiv:2610.13093v1 Announce Type: new Abstract: Autoregressive robot policies rely on action tokenizers to convert continuous action chunks into compact sequences of discrete prediction targets. Exist

safetyarxiv-cs-ro

12 Oct 2026

Recover, Discover, Plan: Learning Skills and Concepts from Robot Failures

arXiv:2606.18328v2 Announce Type: replace Abstract: Intelligent robots should not only recover from failures, but also acquire the abstract knowledge needed to avoid them in the future. While reinforc

Tutorials

Recovering Irreducible Three-Body Interactions with Lagrangian Neural Networks

arXiv:2610.13292v1 Announce Type: new Abstract: Lagrangian Neural Networks (LNNs) learn mechanical systems from trajectory data by parameterizing a scalar Lagrangian and deriving the dynamics through

tutorialsarxiv-cs-lg

Agents

Recurrent Harness for Agentic Continual Learning

arXiv:2610.12668v1 Announce Type: cross Abstract: Language model agents increasingly operate over long interaction streams, requiring online adaptation to distribution shifts through continual learnin

agentsarxiv-cs-ai

REDaCT: Collapse-Free Unlearning in Large Reasoning Models

arXiv:2610.12769v1 Announce Type: cross Abstract: Unlearning in large reasoning models (LRMs) requires removing forget-set information from both the reasoning trace and the final answer. Existing appr

REFLECT: Role-Aware Detection of Sentiment, Emotion, Politeness, and Formality

model-releasesarxiv-cs-cl

arXiv:2610.13797v1 Announce Type: new Abstract: Detecting communicative meaning in dialogue requires modeling not only lexical content but also the participant-role structures through which sentiment,

Reflect-VLA: Internalizing Reflective Guidance via Dual-Path On-Policy Self-Distillation for Autonomous Driving

arXiv:2610.13453v1 Announce Type: new Abstract: Reinforcement Learning (RL) substantially improves planning performance in autonomous-driving Vision-Language-Action (VLA) models. However, existing RL

Agents

Reflective Prompt Optimization of a Deep-Research Agent: A Topic-Disjoint, Multi-Seed Protocol for Measuring Transferable Gains and Prompt-Level Overfitting

arXiv:2610.12601v1 Announce Type: new Abstract: Prompt optimization is an attractive alternative to reinforcement learning for adapting language-model agents, since it is cheap and produces human-read

agentsarxiv-cs-cl

Reflex: Visually Grounded Reactive Humanoid Control

arXiv:2610.12772v1 Announce Type: new Abstract: Humans effortlessly react to the world; they adeptly return a tennis shot, catch a falling cup, step aside from a passing cart, or pass a box tossed dur

Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values

arXiv:2506.11849v3 Announce Type: replace-cross Abstract: With origins in game theory, probabilistic values like Shapley values, Banzhaf values, and semi-values have emerged as a central tool in expla

Applications

RegulaTutor: A Theory-Informed Framework for Long-Term Personalized Learning

arXiv:2610.13399v1 Announce Type: new Abstract: Long-term personalized tutoring requires language models to translate a learner's evolving history into appropriate instructional support. Existing LLM-

applicationsarxiv-cs-ai

Reinforcement Learning via Fixed-point Flow Matching

arXiv:2610.12848v1 Announce Type: new Abstract: In maximum entropy and behavior-constrained reinforcement learning (RL), the optimal policy is given by a Boltzmann distribution. Generating samples fro

safetyarxiv-cs-lg

REMM: Revisable Embodied Memory for Manipulation

arXiv:2610.12710v1 Announce Type: new Abstract: Long-horizon manipulation requires robots to retain task-relevant history while revising conclusions no longer supported by physical evidence. Retaining

ReplaySSM: Cache SSM Inputs, Not State

arXiv:2610.13778v1 Announce Type: cross Abstract: State-space models (SSMs) maintain a fixed-size recurrent state, but reading and writing it at every decoding step can bottleneck hybrid models. This

Representation Alignment from a Few Paired Data via Distilled Optimal Transport

arXiv:2610.12781v1 Announce Type: new Abstract: Aligning two independently pretrained unimodal encoders typically demands millions of paired examples. In this paper, we study the regime where only N s

RESCUE: Is This Alarm Worth Acting On? Counterfactual Evaluation of VLA Runtime Monitors

arXiv:2610.13516v1 Announce Type: cross Abstract: Runtime failure monitors for robot policies are typically evaluated by how accurately they distinguish failed from successful executions. Yet an accur

Applications

ReSFlow: Rectifying Categorical Flows on Statistical Manifolds for One-Step Generation

arXiv:2610.13225v1 Announce Type: cross Abstract: Generative modeling for discrete data has been significantly advanced by learning continuous vector fields on the statistical manifolds to transport s

applicationsarxiv-cs-ai

Rethinking Relative Policy Differences Transfer of On-Policy Distillation

arXiv:2610.13205v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a target policy on its own rollouts using token-level supervision from a stronger teacher, but typically relies on t

safetyarxiv-cs-lg

Rethinking the Roles of Diffusion and Decoding: Predictive-State Flows for Parallel Language Generation

model-releasesarxiv-cs-cl

arXiv:2610.12898v1 Announce Type: new Abstract: In continuous diffusion language models (DLMs), latents generated by the diffusion prior are mapped almost deterministically to tokens, either by a deco

Retractions Revisited: A Replication, Extension, and Mechanistic Evaluation of Linguistic Obfuscation Effects in Fraudulent Science

arXiv:2610.13678v1 Announce Type: new Abstract: Prior work suggests fraudulent scientists write their articles with higher rates of linguistic obfuscation than genuine scientists, with a possible mech

researcharxiv-cs-cl

Retrieval-Augmented Multimodal Language Model with Heterogeneous Evidence Integration for Clinical Prognosis

arXiv:2610.13510v1 Announce Type: new Abstract: Clinical prognosis requires integrating structured measurements, physiological waveforms, longitudinal history, and population context. We introduce PRI

Returning to Development States: When Full Sandbox Snapshots Help Coding Agents

arXiv:2610.13841v1 Announce Type: new Abstract: Coding agents often make useful progress before they fail, but retry-from-scratch discards the machine state created along the way. This makes failure r

Applications

Revisiting Accent Classification with DistilHuBERT: Speaker-Disjoint Evaluation and Cross-Corpus Generalization

arXiv:2610.13440v1 Announce Type: cross Abstract: Recent accent classification systems can achieve high accuracy in standard in-corpus evaluations. However, when speakers overlap between the training

applicationsarxiv-cs-cl

Revisiting Tabular Deep Regression: Objectives and the Limits of Global Early Stopping

arXiv:2610.13909v1 Announce Type: cross Abstract: While deep learning models for tabular data have recently received significant research attention, the choice of objective functions for regression ta

Reward Hacking as a Transmissible Strategy in Multi-Agent Coding Systems

arXiv:2610.12822v1 Announce Type: new Abstract: Multi-agent systems are increasingly used to solve coding tasks by coordinating agents that share code and plans. These agents are often optimized with

Robot-WATCHDOG : failure detection through object-centric graph representation

model-releasesarxiv-cs-ro

arXiv:2610.13403v1 Announce Type: new Abstract: Reliable real-time failure detection is critical for deploying learned robotic policies, yet defining failures explicitly is infeasible in open-world se

Robust and Scalable UAV-UGV Planning for Aerial Monitoring under Energy and Precedence Constraints

arXiv:2610.12670v1 Announce Type: new Abstract: We consider planning for unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV) teams in aerial monitoring missions with ordering requirements

researcharxiv-cs-ro

Robust Langevin Sampling under State-Dependent Heavy-Tailed Noise with Applications to LLM Fine-Tuning

arXiv:2610.12865v1 Announce Type: new Abstract: Existing convergence guarantees for non-log-concave sampling with stochastic gradient Langevin Monte Carlo (SG-LMC) typically assume globally Lipschitz

Robustness of Reinforcement Learning-Based Congestion Management in Low-Voltage Grids

arXiv:2607.16004v2 Announce Type: replace-cross Abstract: Increases in photovoltaic generation, charging of electric vehicles and heat-pump demand challenge operating limits in low-voltage distributio

RoleWorld: Knowledge Transfer in World Modeling with Functional Role Abstractions

arXiv:2610.13172v1 Announce Type: new Abstract: World models enable large language model (LLM) agents to anticipate action effects and make informed decisions. For generalization, it is desirable for

Rollout-Time Intervention: Unlocking Agentic Reinforcement Learning Beyond Policy Limits

arXiv:2610.13438v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving large language model (LLM) agents, enabling stronger reasoning, planning, and to

RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance

arXiv:2602.00183v2 Announce Type: replace-cross Abstract: Deep neural networks are highly susceptible to backdoor attacks, yet most defense methods to date rely on balanced data, overlooking the perva

safetyarxiv-cs-lg

RSI-Anything: Unlocking Recursive Self-Improvement with World Models

arXiv:2610.13912v1 Announce Type: new Abstract: Recursive self-improvement (RSI) aims to transform interaction experience into persistent improvements, yet external feedback is costly and world-model

safetyarxiv-cs-cl

S-Space: Exploring Spatial Workspace in Multimodal Language Models

arXiv:2610.13527v1 Announce Type: cross Abstract: Multimodal language models (MLLMs) exhibit promising spatial reasoning capabilities, yet the internal mechanisms supporting them remain poorly underst

researcharxiv-cs-cl

S^3R: Fast and Faithful RL Rollouts via Self-Sparse Speculative Decoding

model-releasesarxiv-cs-cl

arXiv:2610.13202v1 Announce Type: cross Abstract: Fast rollout generation for long-context reinforcement learning with verifiable rewards (RLVR) requires reducing KV-cache traffic without changing the

SafeDiSTL: Decomposing Joint Constraints for Safe Multi-Agent Reinforcement Learning

arXiv:2610.13737v1 Announce Type: cross Abstract: Cooperative multi-agent tasks often impose constraints on a shared objective or collective safety. A team level violation cost function can measure th

Same Query, Different Answer: Run-to-Run Variance in Semantic Query Processing

arXiv:2610.13823v1 Announce Type: cross Abstract: Semantic query engines ask a large language model (LLM) to judge individual rows, and benchmarks compare these engines on the quality of a few executi

Sample-Adaptive Zeroth-Order Post-Training

arXiv:2610.12566v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization offers a memory-efficient alternative to backpropagation for fine-tuning large language models. However, existing ZO meth

Hardware

Sampling-based Kinodynamic Planning with World Models

arXiv:2610.12910v1 Announce Type: new Abstract: Visual world models predict the consequences of actions from images, but planning with them is typically done by optimizers such as CEM and MPPI. Howeve

hardwarearxiv-cs-ro

SAP-CoPE: Social-Aware Planning using Cooperative Pose Estimation with Infrastructure Sensor Nodes

arXiv:2504.05727v3 Announce Type: replace Abstract: Autonomous mobile robots must operate smoothly in human-populated indoor environments, where onboard-only sensing suffers from limited perception ra

Hardware

SBNO : Schrodinger Bridge Neural Operator for the Forward and Inverse Problems under Missing Information

arXiv:2610.13317v1 Announce Type: new Abstract: Partial differential equation (PDE) surrogate modeling often relies on either dense observations or access to governing equations/physics constraints. I

hardwarearxiv-cs-lg

Scalable Circuit Learning for Interpreting Large Language Models

arXiv:2606.16939v2 Announce Type: replace-cross Abstract: A prominent research direction in mechanistic interpretability is learning sparse circuits over LLM components to reveal how they jointly prod

Scalable Learning of Determinantal Point Processes with Kernel-Structured Interactions

model-releasesarxiv-cs-lg

arXiv:2610.12829v1 Announce Type: cross Abstract: Determinantal point processes (DPPs) on a finite set are probability models that exhibit repulsion where inter-item similarities are encoded by a posi

Scalable Sparse Autoregressive Variational Inference for Non-Gaussian Spatial Fields

arXiv:2610.13656v1 Announce Type: cross Abstract: Latent field models are essential for spatial statistics, but the posterior distribution of the latent field, even with a Gaussian process (GP) prior,

Local Ai

Scaling Agentic Data for Long-Horizon Terminal Intelligence

arXiv:2610.13166v1 Announce Type: new Abstract: Terminal agents are moving beyond local operations toward completing real-world professional tasks. Short trajectories can demonstrate commands and tool

local-aiarxiv-cs-cl

Agents

Scaling Empowered Agents

arXiv:2610.13002v1 Announce Type: new Abstract: Empowerment measures the capacity of an agent to actively control its environment. In this work, we explain the connection between skill learning and em

agentsarxiv-cs-ai

Scaling RNA Foundation Models through Iterative Refinement

model-releasesarxiv-cs-lg

arXiv:2610.13106v1 Announce Type: new Abstract: Biological function in RNA is encoded across scales, from local sequence motifs to long-range structural dependencies. Conventional RNA foundation model