All entries

Reserve-Aware Contrast Certificates for Conservative Bandits with Uncertain Baselines

arXiv:2609.39106v1 Announce Type: new Abstract: Conservative bandits must improve an incumbent policy without exhausting a prescribed performance budget. When the incumbent is uncertain, separately bo

Content type

All Blog X Post Paper YouTube Reddit GitHub

Residual Wrench Certification and Margin-Aware Control Synthesis for Aerial Physical Interaction

DGX agent

arXiv:2609.38707v1 Announce Type: new Abstract: We develop a task-relative framework for certifying residual wrench authority after hover and contact loading in multirotors with bounded actuators. Usi

researcharxiv-cs-ro

1 Oct 2026

ResidualKV: Residual-Based KV Cache Compression for Efficient Long-Context Inference

arXiv:2602.08005v2 Announce Type: replace-cross Abstract: Efficient long-context inference faces two coupled bottlenecks: KV-cache memory grows linearly with context length, while attention computatio

Residuals Are Not Enough: Limits of Physics-Informed Pre-Training for Scientific Foundation Models

arXiv:2503.19081v2 Announce Type: replace Abstract: Scientific foundation models (SciFMs) aim to learn generalizable representations of physical systems governed by partial differential equations (PDE

tutorialsarxiv-cs-lg

Restoring without Forgetting: Filter-Level Continual Image Restoration via Parameter-Space Integrated Gradients

model-releasesarxiv-cs-cv

arXiv:2609.38591v1 Announce Type: new Abstract: Adapting image restoration models to a stream of new tasks without revisiting past data remains challenging due to catastrophic forgetting. In this work

RESUME: Recurrent State Updates from Motion and Residual Signals for Efficient Video Language Modeling

arXiv:2609.39563v1 Announce Type: new Abstract: Existing video language models encode sampled RGB frames independently, so a long video must either exhaust the token budget or drop the changes between

researcharxiv-cs-cv

ReTaCo: Residual-Target Control for On-Policy Distillation

arXiv:2609.39275v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own generated prefixes with token-level teacher feedback, but transmitting or storing the teacher's

safetyarxiv-cs-lg

Local Ai

Retargeting Motions to Diverse Skeletons via Learnable Flattening

arXiv:2609.38578v1 Announce Type: cross Abstract: Cross-structural motion retargeting aims to transfer motion between different skeletal topologies. Despite recent progress, existing state-of-the-art

local-aiarxiv-cs-ai

Rethinking Generative Image Compression at Extremely Low Bitrates

model-releasesarxiv-cs-cv

arXiv:2609.39315v1 Announce Type: new Abstract: Generative image compression produces visually plausible reconstructions at low bitrates, yet their behavior as the rate approaches zero remains largely

Rethinking Legibility in Social Robot Hallway Navigation: Impact of Intent Representation and Human Distraction

arXiv:2609.40158v1 Announce Type: new Abstract: We focus on legible robot motion generation in social navigation settings. Legibility in human-robot interaction (HRI) is often described as the propert

Rethinking Multi-Image Re-Representation in Multi-Image Understanding

arXiv:2609.39363v1 Announce Type: cross Abstract: Multi-image understanding requires MLLMs not only to recognise the content of individual images, but also to organise visual evidence distributed acro

RetroGEF: Dynamic Graph Edit Flow for Single-Step Retrosynthesis

arXiv:2609.38484v1 Announce Type: new Abstract: Retrosynthesis enables the discovery of viable synthetic routes to target molecules. It plays a central role in modern drug discovery and materials desi

Revisiting On-policy Adversarial Black-Box Distillation: Calibrating Groupwise Reward Geometry for Effective Advantage Construction

arXiv:2609.39757v1 Announce Type: cross Abstract: Black-box distillation is a practical route for transferring capabilities from API-accessible large language models that expose only text outputs into

safetyarxiv-cs-cv

Revisiting scaling laws for reward optimization

arXiv:2609.38526v1 Announce Type: cross Abstract: Scaling laws for optimization against reward models in AI alignment have pinned down how performance depends on optimization effort---measured by a KL

ReWAM: Reciprocal World Action Models for Interactive Autonomous Driving

arXiv:2609.39245v1 Announce Type: new Abstract: In interactive scenarios, an autonomous driving system is required to generate ego actions under the influence of other agents' behaviors. Existing Worl

RiboUnmix: Learning Shared Translational Dynamics from Biased and Noisy Ribo-seq Measurements

arXiv:2609.39644v1 Announce Type: new Abstract: Ribosome profiling (Ribo-seq) measures ribosome distributions along mRNAs, but observed occupancy profiles also contain experiment-specific distortions

Agents

Richard: Voice-First Mobile Interaction for Persistent Tasks

arXiv:2609.39976v1 Announce Type: cross Abstract: Mobile terminals need to provide application and network services while supporting users' control over their attention. We explore voice-first interac

agentsarxiv-cs-ai

Riemannian Flow Models with Reinforcement Learning for Molecular Crystal Structure Prediction

arXiv:2609.39773v1 Announce Type: new Abstract: Crystal structure governs material properties, making crystal structure prediction (CSP) a fundamental problem in materials science. Generative models a

Right Answer, Wrong Mechanism: Detecting Pernicious Divergence in Causal Interventions

arXiv:2609.39243v1 Announce Type: new Abstract: Causal interventions such as activation patching and distributed alignment search (DAS) are the main tool for making mechanistic claims about neural net

Right Answers, Costly Models: The Efficiency Gap in LLM-based Optimization Modeling

arXiv:2609.38884v1 Announce Type: cross Abstract: Optimization modeling formulates real-world decision problems as mathematical programs that solvers can use to find optimal decisions. Large language

Right-Wing Rock or Just Rock? A Computational Linguistic Analysis of Frei.Wild

arXiv:2609.39460v1 Announce Type: new Abstract: Rechtsrock is a subgenre of rock music that spreads right-wing ideology, often instrumentalized to recruit adolescents into the radical scene. Monitorin

researcharxiv-cs-cl

Applications

Rising Multi-Armed Bandits with Known Horizons

arXiv:2602.10727v3 Announce Type: replace Abstract: Rising Multi-Armed Bandits (RMABs) model sequential decision problems where each arm's expected reward improves with repeated pulls. In such problem

applicationsarxiv-cs-lg

Risk-Aware Adaptive Evaluation: Finding High-Impact Failures Under Limited Budgets

arXiv:2609.38914v1 Announce Type: new Abstract: Evaluating interactive agents is expensive. Agent behavior is stochastic, so reliability must be measured over repeated trials, but failures are rare an

RL-Guided PAC-NMPC for Probabilistically-Safe Perception-Based Navigation in Unknown Environments

arXiv:2609.39854v1 Announce Type: new Abstract: In this paper, we present an approach for combining stochastic nonlinear model predictive control (SNMPC) and reinforcement learning (RL) to enable prob

RLTL;DR: Self-Improvement by Internalizing Self-Generated Feedback

The common paradigm of reinforcement learning with verifiable rewards (RLVR) is to let agents make multiple attempts at a task, and optimize towards the successful ones. This becomes problematic in th

safetyapple-ml-research

RoboAssist: Interactive Human-Humanoid Planning for Long-Horizon Surgical Assistance

arXiv:2609.39384v1 Announce Type: new Abstract: Long-horizon surgical assistance requires humanoid robots to coordinate with evolving human activities while maintaining safety across planning and exec

RoboCoach: World Models as Active Coaches for Compositional Robot Skills

arXiv:2609.39685v1 Announce Type: cross Abstract: Long-horizon robot manipulation reuses skills across many task compositions, but improving these compositions with additional end-to-end demonstration

Robust and Learned Online Matching in Growing Trees

arXiv:2609.40077v1 Announce Type: cross Abstract: We study irrevocable maximum-cardinality matching in trees revealed by successive leaf attachments, with a known horizon and an exogenous growth law t

Robust Budget Pacing with a Single Sample

arXiv:2302.02006v2 Announce Type: replace Abstract: Major Internet advertising platforms offer budget pacing tools as a standard service for advertisers to manage their ad campaigns. Given the inheren

tutorialsarxiv-cs-lg

Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions

arXiv:2609.38263v1 Announce Type: cross Abstract: Feature selection in neural networks remains a challenging problem, particularly in the presence of noisy or contaminated data. LassoNet is a recent a

Robust Risk-Sensitive Reinforcement Learning from Corrupted Human Feedback

arXiv:2609.38938v1 Announce Type: new Abstract: Reinforcement learning with human feedback (RLHF) learns from human comparisons, which can be corrupted or deliberately manipulated. This paper studies

Applications

Robust Transfer Learning for Paper ECG Recognition

arXiv:2609.39581v1 Announce Type: cross Abstract: Paper ECG recognition is challenging because real-world ECG images vary in layout, physical artifacts, and label availability. We introduce RobECG-CL,

applicationsarxiv-cs-ai

Local Ai

Robust Wake-Up Word Detection by Two-stage Multi-resolution Ensembles

arXiv:2310.11379v2 Announce Type: replace-cross Abstract: Voice-based interfaces rely on a wake-up word mechanism to initiate communication with devices. However, achieving a robust, energy-efficient,

local-aiarxiv-cs-cl

Robustifying Asynchronous SGD via Soft Throttling

arXiv:2609.39357v1 Announce Type: new Abstract: Asynchronous SGD is a popular algorithm for distributed learning where each client's gradient update is applied on arrival. This leads to a speed-up, bu

Role-Adaptive Policy Optimization for Offline Reinforcement Learning

arXiv:2609.40149v1 Announce Type: new Abstract: Policy regularization in offline reinforcement learning balances policy improvement against reliance on uncertain value estimates. This balance can diff

safetyarxiv-cs-lg

Role-guided Speaker Deletion Verification in Clinical Psychiatry Speech Recordings with Audio Language Models

arXiv:2609.38491v1 Announce Type: new Abstract: Clinical research in psychiatry increasingly relies on large scale collection of spoken language data to identify acoustic and linguistic biomarkers. Ye

RoPE at the End of Its Rope? Theory, Diagnosis, and Mitigation of Long-Context Failures

model-releasesarxiv-cs-cl

arXiv:2609.39929v1 Announce Type: cross Abstract: Long-context failures of RoPE-based language models can arise from RoPE's intrinsic tradeoff between maintaining stable token preferences and distingu

RouteRec: Behavior-Guided Sparse Routing for Sequential Recommendation

arXiv:2609.39007v1 Announce Type: cross Abstract: Sessionized interaction histories contain behavioral patterns that can improve sequential recommendation. However, existing models process all session

tutorialsarxiv-cs-lg

Routing Probes Can Improve Without New Information: An Exact-Null Audit of Uncertainty Beyond Model Outputs

arXiv:2609.38956v1 Announce Type: new Abstract: Routing signals of modern vision transformers -- expert gates, attention-residual weights and halting scores -- often improve probes that predict whethe

researcharxiv-cs-ai

RSI-Master: Structuring Experiments to Guide Autonomous Model Improvement

arXiv:2609.35561v2 Announce Type: replace Abstract: Recursive self-improvement (RSI) seeks to enable AI systems to participate in improving their own capabilities. A concrete pathway is autonomous mod

RSIGame: Autonomous Agentic Game Development with Recursive Self-improvement

model-releasesarxiv-cs-cl

arXiv:2609.39045v1 Announce Type: new Abstract: Recent advances in large language models have made automatic game generation increasingly feasible, yet reliably improving generated games beyond a play

RW-Flow: One-Step Generation on Compact Manifolds via Wasserstein Gradient Flows

arXiv:2609.39271v1 Announce Type: new Abstract: Manifold-valued data, and consequently the distributions they induce, are prevalent across many domains, ranging from the locations of geospatial events

Safety Monitors Mostly Catch What the Model Already Refuses

arXiv:2609.05797v3 Announce Type: replace Abstract: Safety monitors are evaluated by recall on harmful prompts, regardless of whether the target model would answer them. Yet a monitor matters most on

safetyarxiv-cs-cl

Safety of Latent Communication in Multi-Agent Systems

arXiv:2609.39788v1 Announce Type: new Abstract: Latent communication enables multi-agent systems to exchange information directly in internal representation space, reducing the token, computation, and

SAGE: Salient Factor Discovery and Generation with Visual Foundation Representations

arXiv:2609.39635v1 Announce Type: new Abstract: Given a target dataset, such as faces with eyeglasses, and a background dataset, such as faces without, contrastive analysis separates extit{salient} fa

tutorialsarxiv-cs-cv

Industry

Salesforce to acquire AI customer research startup Listen Labs in reported $2B deal

Salesforce Inc. has signed a definitive agreement to acquire artificial intelligence customer research startup Listen Labs Inc., three weeks after reports first surfaced that the two companies were in

industrysiliconangle

Same Loss, Different Gradients

arXiv:2609.38786v1 Announce Type: new Abstract: Differentiable learning typically assumes that the scalar objective evaluated in the forward pass and the gradient supplied to the optimizer in the back

Say, Echo, Do: Strategic Narratives and Revealed Positioning in Financial Markets

arXiv:2609.38545v1 Announce Type: cross Abstract: Machine-learning signals built from financial text treat what institutions say, and what the media repeat, as evidence about value. But whoever shapes