All entries

Performative Prediction with Selective Labels

arXiv:2610.08272v1 Announce Type: new Abstract: Many social applications of machine learning exhibit performative effects: population behavior changes in response to deployed models. Performative pred

safetyarxiv-cs-lg

PERSIST: Who-What-When Memory Across Sessions for Full-Duplex Spoken Dialogue

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2610.07725v1 Announce Type: new Abstract: Modern voice assistants may be shared by multiple users and should be able to answer questions about earlier conversations such as 'When did I originall

model-releasesarxiv-cs-ai

7 Oct 2026

Persistent Memory in Multi-Agent LLM Inference: What It Costs, What It Buys, and When You Can Tell

arXiv:2610.07782v1 Announce Type: new Abstract: Decomposing long-context inference across cooperating agents bounds the active KV cache per call rather than total evidence, which matters when KV-cache

agentsarxiv-cs-ai

Personal-Agent Mediated Recommendation with Cross-Platform User History

arXiv:2610.07588v1 Announce Type: new Abstract: Modern recommendation is shifting from platform-centric personalization toward user-governed personalization, where a personal LLM agent can act on the

Local Ai

PHBA: Prefix-State Hybrid Block Attention

arXiv:2610.08527v1 Announce Type: new Abstract: Hybrid architectures combining linear sequence models with softmax attention provide an effective balance between efficient long-context modeling and pr

local-aiarxiv-cs-lg

PhoneBot: A Low-Cost Open Humanoid Robot Platform Reusing Smartphones

arXiv:2610.08737v1 Announce Type: new Abstract: The adoption of humanoid robots in education and research remains limited by high hardware costs, complex sensing systems, and substantial computational

applicationsarxiv-cs-ro

Physical Twins: Accelerating and Enabling Robot Learning with Phantom Platforms

arXiv:2610.06929v1 Announce Type: new Abstract: Improvements in human-robot physical interaction (pHRI) can have major implications for physical therapy, search and rescue, and telemedicine. However,

safetyarxiv-cs-ro

PhysLDM: Latent Diffusion for High-Fidelity Deformable Simulation

arXiv:2610.07609v1 Announce Type: new Abstract: Neural simulation of high-fidelity deformable bodies is a foundational challenge in computer graphics and physical AI. Long-horizon prediction for high-

PhysTacGen: Physics-Aware Visual-Tactile Sensor Image Generation

arXiv:2610.08068v1 Announce Type: new Abstract: Realistic physical interaction is a cornerstone of embodied intelligence, yet collecting paired visual--tactile data remains costly. Visual-to-tactile s

safetyarxiv-cs-cv

PIE-PS: Photometric Stereo from Physical Irradiance Event Streams

arXiv:2610.08188v1 Announce Type: new Abstract: Event cameras record asynchronous log-image-irradiance changes with microsecond latency and high dynamic range. These properties are useful for photomet

PlaySuite: A Large-Scale Benchmark for Interactive Visual Intelligence

arXiv:2610.07127v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models yield strong performance on static perception and reasoning benchmarks, yet such evaluations largely o

PlotPick: AI-powered batch extraction of numerical data from scientific figures

model-releasesarxiv-cs-cv

arXiv:2605.06021v2 Announce Type: replace Abstract: Systematic reviews and meta-analyses often need numerical data reported only in figures, and extracting them with interactive digitisers usually req

Polar: LLM-Powered Synthesis of Real-World Cyber Evidence for Prioritization and Mitigation

arXiv:2610.07298v1 Announce Type: cross Abstract: Cyber threat analysis increasingly depends on evidence distributed across vendor advisories, vulnerability databases, and threat intelligence sources.

applicationsarxiv-cs-ai

POLAR: Ontology-Guided Risk Prevention for Tool-Calling LLM Agents

arXiv:2610.08082v1 Announce Type: new Abstract: LLM tool-use agents operate in dynamic environments where many actions carry operational risk. However, most safety mechanisms react only after errors m

safetyarxiv-cs-ai

PolarScale: A Physics-Grounded Benchmark for Radiometrically Consistent RGB-to-Stokes Estimation

model-releasesarxiv-cs-cv

arXiv:2610.08346v1 Announce Type: new Abstract: Polarization imaging provides physical cues beyond intensity imaging but typically requires specialized hardware. Recent methods infer polarization from

Post-Grasp Kinematic Repair for Robotic Insertion via Object-in-Gripper Reorientation

arXiv:2610.08421v1 Announce Type: new Abstract: A stable grasp does not guarantee kinematically feasible robotic insertion because the object-in-gripper transform may force the robot towards singulari

researcharxiv-cs-ro

Post-Training Semantic Lifting for 3D Gaussian Splatting: Separating Detector, Lifting and Representation Error

arXiv:2610.08756v1 Announce Type: new Abstract: The same Gaussian of a 3D Gaussian Splatting model is seen from many views, and these views do not always agree on the class it belongs to. The Gaussian

Practical Feasibility of Gradient Inversion Attacks in Federated Learning

arXiv:2508.19819v3 Announce Type: replace-cross Abstract: Gradient inversion attacks are often presented as a serious privacy threat in federated learning, with recent work reporting increasingly stro

applicationsarxiv-cs-ai

Tutorials

Predicting kernel regression learning curves from only raw data statistics

arXiv:2510.14878v3 Announce Type: replace-cross Abstract: We study kernel regression with common rotation-invariant kernels on real datasets including CIFAR-5m, SVHN, and ImageNet. We give a theoretic

tutorialsarxiv-cs-ai

Prediction-powered inference for time series across space

arXiv:2610.08715v1 Announce Type: cross Abstract: The following motif is common in spatiotemporal settings: we have a sequence of covariate and label pairs observed for a relatively short, recent time

safetyarxiv-cs-lg

Preserving Unstable Modes Through Inverse Dynamics in JEPA World Models

arXiv:2610.07540v1 Announce Type: new Abstract: Robotic systems often exhibit unstable modes, along which small perturbations and disturbances can cause unbounded growth unless corrected through feedb

researcharxiv-cs-lg

Principled Under Pressure: Post-Training Decides Whether LLMs Act on Their Own Moral Judgment

arXiv:2610.08670v1 Announce Type: cross Abstract: Language models increasingly act as agents. An agent that says an action is wrong and then takes it anyway is a different failure from one that does n

Principles that Guide, Actions that Inform: Agent Evolution via Knowledge Abstraction

arXiv:2610.06964v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capabilities in interactive environments, yet their ability to continually evolve from experi

Privileged Context as Drift in On-Policy Self-Distillation

model-releasesarxiv-cs-lg

arXiv:2610.07842v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a language model to match a copy of itself conditioned on privileged context. Existing work varies what privil

Local Ai

ProactiveVLA: Augmenting Embodied Memory through Proactive Environment Exploration

arXiv:2610.06999v1 Announce Type: new Abstract: Rapid adaptation to a new environment requires a robot to acquire useful knowledge about local objects, states, and interactions from limited experience

local-aiarxiv-cs-ro

Probabilistic Counterfactual Inference for Discrete Outcomes in Gaussian-Process Causal Models

arXiv:2610.08689v1 Announce Type: new Abstract: Counterfactual inference in Gaussian-process structural causal models (GP-SCMs) has been developed primarily for continuous endogenous variables, limiti

researcharxiv-cs-lg

Probabilistic Truly Unordered Rule Sets

model-releasesarxiv-cs-lg

arXiv:2401.09918v2 Announce Type: replace Abstract: Rule set learning has recently been frequently revisited because of its interpretability. Existing methods have several shortcomings though. First,

ProCut: Probabilistic Cutting Topology for Autonomous Electrosurgical Tissue Dissection

arXiv:2610.07515v1 Announce Type: new Abstract: Accurately modeling and tracking the deformation of soft tissue is critical for a wide range of interventional and surgical procedures. However, current

agentsarxiv-cs-ro

Pronunciation Editing for Finnish Speech using Phonetic Posteriorgrams

arXiv:2507.02115v3 Announce Type: cross Abstract: Synthesizing second-language (L2) speech is potentially highly valued for L2 language learning experience and feedback. However, due to the lack of L2

safetyarxiv-cs-cl

Protective Perturbations Must Survive the Resize: Scale-Robust Image Immunization against Malicious Editing

arXiv:2610.07464v1 Announce Type: new Abstract: Protective perturbations aim to stop malicious instruction-guided editing of personal photos, but they are optimized and evaluated at the editor's worki

ProximalFM: Amortized Proximal Causal Inference under Hidden Confounding

arXiv:2610.08078v1 Announce Type: cross Abstract: Standard causal identification methods often assume no unmeasured confounding and can fail when relevant confounders are unobserved. Proximal causal i

researcharxiv-cs-lg

PRUE: A Practical Recipe for Field Boundary Segmentation at Scale

model-releasesarxiv-cs-cv

arXiv:2603.27101v2 Announce Type: replace Abstract: Large-scale maps of field boundaries are essential for agricultural monitoring tasks. Existing deep learning approaches for satellite-based field ma

Pseudowords as probes: Large Language Models show little of the sublexical sensitivity that governs human pseudoword processing

arXiv:2610.07936v1 Announce Type: new Abstract: Systematicity, the probabilistic mapping of form to meaning, permeates language at all levels, and sublexical cues have been shown to govern human pseud

safetyarxiv-cs-cl

PsyCIDRA: A Dual-Agent Framework for Psychiatric Interviewing and Diagnostic Reasoning

arXiv:2610.07473v1 Announce Type: new Abstract: Large language models show promise in clinical reasoning, but psychiatric interviewing requires guiding an evolving conversation. Their ability to carry

safetyarxiv-cs-ai

PuzzleJAX: A Benchmark for Reasoning and Learning

arXiv:2508.16821v2 Announce Type: replace Abstract: We introduce PuzzleJAX, a GPU-accelerated puzzle game engine and description language designed to support rapid benchmarking of tree search, reinfor

QF3: Fast Flow RL with Filtered Q-Gradients

arXiv:2610.08789v1 Announce Type: cross Abstract: Flow policies have become a standard policy class for learning robot behaviors from demonstrations, but reinforcement learning is still critical for i

safetyarxiv-cs-lg

QiYao-I: A Manifold Based Foundation Model for Irregular Multivariate Time Series Forecasting

arXiv:2610.06936v1 Announce Type: new Abstract: Irregular multivariate time series forecasting is a challenging yet important problem in real-world applications, where observations are often irregular

applicationsarxiv-cs-lg

Quadratic Direct Forecast for Training Multi-Step Time-Series Forecast Models

arXiv:2511.00053v2 Announce Type: replace-cross Abstract: The design of learning objectives is central to training time-series forecasting models. Existing learning objectives such as mean squared err

researcharxiv-cs-ai

Quality-Aware Self-Correcting Speech Translation on an Edge Device

arXiv:2610.07545v1 Announce Type: new Abstract: We present a fully offline speech-to-speech translation pipeline that runs on a Jetson Nano (4 GB) and corrects its own weak translations without retrai

researcharxiv-cs-cl

Quantifying Cross-Lingual Transfer in Paralinguistic Speech Tasks

arXiv:2603.08231v2 Announce Type: replace-cross Abstract: Paralinguistic speech tasks are often considered relatively language-agnostic, as they rely on extralinguistic acoustic cues rather than lexic

researcharxiv-cs-cl

Quantifying the Gap between Understanding and Generation within Unified Multimodal Models

model-releasesarxiv-cs-cl

arXiv:2602.02140v2 Announce Type: replace Abstract: Recent advances in unified multimodal models (UMM) have demonstrated remarkable progress in both understanding and generation tasks. However, whethe

Quantization Effects on Tool-Failure Recovery Vary Across Prompts and Evaluation Designs

arXiv:2610.07781v1 Announce Type: new Abstract: Post-training quantization reduces the cost of deploying language-model agents, but its effect on recovery from temporary tool failures can depend on ho

Quantum Entangled Multimodal Fusion Networks (QEMFN): Resource-Aware Hybrid Vision-Language Fusion via Trainable Entanglement

arXiv:2610.08216v1 Announce Type: new Abstract: Multimodal vision-language systems typically fuse image and text embeddings through classical operators such as concatenation, attention, bilinear pooli

Qubit-centric Transformer for Surface Code Decoding

arXiv:2510.11593v3 Announce Type: replace-cross Abstract: For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across mu

researcharxiv-cs-ai

R2RI: A Multi-View Event and RGB Dataset for Robot-to-Robot Interaction

arXiv:2610.07117v1 Announce Type: new Abstract: Understanding and modeling interactions between autonomous agents is a fundamental challenge in robotics, with broad implications for collaborative syst

agentsarxiv-cs-cv

RA-MoWE: Workflow-Affinity Embeddings for Query Clustering and Agentic Workflow Generation

arXiv:2610.07851v1 Announce Type: new Abstract: Agentic workflows enable large language models (LLMs) to solve complex tasks by coordinating reasoning, tool use, and verification. However, a workflow

agentsarxiv-cs-ai

RACE-FPP: A Robust AI-assisted Characterisation Enhancement for Fringe Projection Profilometry

arXiv:2610.08213v1 Announce Type: new Abstract: Fringe Projection Profilometry (FPP) requires precise system characterisation to achieve reliable three-dimensional (3D) reconstructions; however, chara

RACER: Residual-Adaptive Closed-Loop Estimation for Sampling-Based Planning in Wheeled-Quadruped Racing

arXiv:2610.07409v1 Announce Type: new Abstract: We present RACER, a hierarchical control framework for wheel-based quadruped racing that combines an MPPI planner with a learned residual dynamics model

safetyarxiv-cs-ro