Search: “framework”

Prediction-Powered Data Fusion for Treatment Effect Estimation

arXiv:2610.12332v1 Announce Type: cross Abstract: Randomized controlled trials (RCTs) identify treatment effects without confounding but are often small, whereas observational studies (OBS) are large

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Predictive Multiplicity in Cell-Fate Assignment: Label-Free Rashomon Sets and the Limits of Per-Cell Certification

DGX agent

arXiv:2610.11185v1 Announce Type: new Abstract: Single-cell trajectory inference maps transcriptomic measurements onto developmental continua, yet configurations that fit the data equally well can ass

researcharxiv-cs-lg

9 Oct 2026

Probability-Signature Dynamics: Unpacking Modular Addition Learning Within Two-Layer Networks

arXiv:2610.11833v1 Announce Type: new Abstract: Neural networks trained on modular addition tasks often develop Fourier-structured representations that support exact generalization. While prior work h

Proof-of-Use: Mitigating Tool-Call Hacking in Deep Research Agents

arXiv:2510.10931v3 Announce Type: replace Abstract: While reinforcement learning (RL) enhances their ability to plan and reason across retrieval steps, we identify a critical failure mode in this sett

Puffin: Probabilistic Learning of Spatial Detail From Coarse Observations

arXiv:2610.11914v1 Announce Type: new Abstract: High-resolution socioeconomic variables are important for applications such as urban planning, public health, disaster response, and resource allocation

researcharxiv-cs-lg

PXtal: Learning to Align Powder X-Ray Diffraction and Crystal Structures under Information Asymmetry across Modalities

arXiv:2610.10653v1 Announce Type: new Abstract: Scientific multimodal learning commonly assumes that paired views are comparably informative. Powder X-ray diffraction (PXRD) makes this mismatch explic

safetyarxiv-cs-lg

RAGenome: Scaling Retrieval-Based Genomic Language Models to Long Contexts

arXiv:2610.11761v1 Announce Type: new Abstract: The genome holds the blueprint that governs the biological properties of the cell. Consequently, advancing our knowledge of genomic function is crucial

researcharxiv-cs-lg

RaReCache: Bridging the Gap in Cross-Model KV Cache Reuse via Rank disagreement-based Selective Recomputation

arXiv:2610.11358v1 Announce Type: new Abstract: Cross-model KV-cache reuse remains a key challenge in modern LLM serving. Coding agents and multi-model systems increasingly route a shared context acro

REACT: Rolling Denoising and Dual Decoupling for Reactive Robot Control with VLA Models

arXiv:2610.12007v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) models generate action chunks for temporally coherent robot motion, but chunked control creates a fundamental

Recurrent Self-Improvement: Dynamic Cross-Loop On-Policy Distillation for Looped Language Models

arXiv:2610.10623v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation s

Recursive Self-Improvement through Multi-Agent Self-Supervision

arXiv:2610.12176v1 Announce Type: new Abstract: Recursive self-improvement (RSI) of a model on non-verifiable tasks, such as open-ended research, faces a supervision bottleneck when its outputs exceed

Region-Aware CLS Token Augmentation for Fine-Grained Image Retrieval

arXiv:2610.10991v1 Announce Type: new Abstract: Image retrieval methods often rely on a single global semantic descriptor extracted from an image, e.g., the [CLS] token in vision transformers. However

safetyarxiv-cs-cv

RESETTLE: Robotic Recovery through Disagreement-Triggered Retrieval and Efficient Corrective Control

arXiv:2610.12185v1 Announce Type: new Abstract: Reliable robotic manipulation requires timely intervention to correct emerging deviations and restore progress after execution errors. However, recovery

safetyarxiv-cs-ro

ReSI: Recursive Safety Improvement toward Resistant and Resilient AI

arXiv:2610.12233v1 Announce Type: cross Abstract: Recursive self-improvement, the participation of AI systems in improving their own capabilities, is beginning to move from theoretical prospect to pra

ReTeach: Building a Self-Teacher through Multi-Round Reflection and Retry

arXiv:2610.11529v1 Announce Type: new Abstract: Self-distillation can improve reasoning without a separately trained, more capable teacher, but its effectiveness depends on how the self-teacher gains

Hardware

Revisiting Handcrafted Minutiae Detection: A Simple and Effective Open Source Baseline for Modern Fingerprint Workflows

arXiv:2610.11641v1 Announce Type: new Abstract: Handcrafted minutiae detection algorithms remain fundamental to biometric science and forensic practice due to their full auditability, adherence to int

hardwarearxiv-cs-cv

RFChipAgent: Multi-Agentic AI Flow for Analog/RF Chip Design

arXiv:2610.10858v1 Announce Type: cross Abstract: Analog/RF circuits remain the critical interface between digital computation and the physical world, and emerging standards from Wi-Fi 7 to 6G place s

RL-ARC: Calibrating Large Reasoning Models via Reasoning-guided Uncertainty

arXiv:2610.11352v1 Announce Type: new Abstract: Language models (LMs) are commonly trained with Reinforcement Learning with Verifiable Rewards (RLVR) to enhance their reasoning capabilities. However,

Tutorials

RoboAug: One Annotation to Hundreds of Scenes via Region-Contrastive Data Augmentation for Robotic Manipulation

arXiv:2602.14032v2 Announce Type: replace Abstract: Enhancing the generalization of robotic learning in diverse unseen environments remains a fundamental challenge. Existing approaches often rely on l

tutorialsarxiv-cs-ro

RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2510.25257v2 Announce Type: replace Abstract: Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the p

Rubric-CEPR: Self-Evolving Image Editing via Reward-Verified Self-Distillation

model-releasesarxiv-cs-cv

arXiv:2610.12469v1 Announce Type: new Abstract: Instruction-guided image editors have become highly capable, yet improving them further still depends on human-edited training pairs or external reward

Runnable Commit Untangling for Coding Agents

arXiv:2610.11593v1 Announce Type: cross Abstract: Coding agents produce large, tangled patches that mix multiple development purposes, making the code hard to review and maintain. Commit untangling of

Local Ai

S^3Geo: Structure-Semantic Synergistic Learning for Cross-View Geo-Localization

arXiv:2610.11608v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) aims to estimate geographic locations by matching images captured from different viewpoints, such as drone and satell

local-aiarxiv-cs-cv

S4oP: Operator-level Pruning of Structured State Space Models for Resource-Constrained Devices

arXiv:2606.18096v2 Announce Type: replace-cross Abstract: Structured State Space Models (SSMs), including the S4 and S4D architectures, have recently emerged as powerful alternatives to attention-base

Safe, Persistent, and Evolving Agent Harness for Understanding Partially Observable Worlds

arXiv:2610.11552v1 Announce Type: new Abstract: Large language model agents can invoke tools fluently, but enterprise workflows demand more than selecting the right tools: actions must strictly comply

Applications

SafeInferCom: Safe Inference-Time Compute via Verifier-Guided Mid-Generation Intervention for Robotic Task Planning

arXiv:2610.11223v1 Announce Type: cross Abstract: Large Reasoning Language Models (LRLMs) enable multi-step reasoning for robotic task planning, but continued reasoning can overwrite valid intermediat

applicationsarxiv-cs-ai

Local Ai

SatFix: Absolute Visual Localization of UAVs in Satellite Maps from a Single Oblique Image

arXiv:2610.11049v1 Announce Type: new Abstract: We study absolute metric UAV localization within a provided geo-referenced satellite region, recovering continuous map position and viewing heading from

local-aiarxiv-cs-cv

Local Ai

Scalable AI Uncertainty Quantification via Generalized Laplace Active Subspaces

arXiv:2610.11738v1 Announce Type: new Abstract: Reliable uncertainty quantification (UQ) is essential for deploying neural networks in scientific and high-stakes applications, but full Bayesian infere

local-aiarxiv-cs-ai

Scaling Verifiable Environments for Long-horizon Work Agents

arXiv:2610.04906v2 Announce Type: replace-cross Abstract: Work agents operate over digital artifacts to execute professional knowledge-intensive work, requiring training environments that support long

SCORE: Spectral Correlation Estimation for Multivariate Gaussians

arXiv:2610.12096v1 Announce Type: new Abstract: Neural network-based predictive modeling with high-dimensional structured Gaussian targets requires an efficient and numerically stable, yet expressive

researcharxiv-cs-lg

Searching for 'Harmful Refusal': A Psychometric Audit of an AI Safety Benchmark

arXiv:2610.12409v1 Announce Type: new Abstract: Safety benchmarks typically report one overall score for a suite of datasets, each of which may target one or more safety-related attributes, so models

Seeing Through the Glare: A Multi-Source Benchmark and Ocular-Adaptive Pixel MeanFlow for Eyeglass Reflection Removal

model-releasesarxiv-cs-cv

arXiv:2610.10703v1 Announce Type: new Abstract: Eyeglass reflection removal is important across smartphone imaging, video conferencing, and other face-centric visual applications. The task is challeng

Seek-and-View Reasoning for Multi-View Spatial Understanding

arXiv:2610.11810v1 Announce Type: new Abstract: Existing approaches to multi-view spatial reasoning operate largely on sparse input views. Vision-language models (VLMs) are thus restricted to understa

safetyarxiv-cs-cv

Sera: Semantic Representation Aggregation for Reliable and Interpretable Battery Health Forecasting

arXiv:2610.11567v1 Announce Type: cross Abstract: Battery state of health (SoH) forecasting is important for battery management, but remains challenging due to nonlinear degradation and heterogeneity

SFT-as-Context Mitigates Forgetting in Supervised Fine-Tuning

arXiv:2610.11132v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) equips large language models (LLMs) with specialized capabilities, but often comes at the cost of forgetting the general

Tutorials

Shape irregularity of Life-Like Network Automaton rules as an indicator of classification performance

arXiv:2610.10867v1 Announce Type: new Abstract: Complex Network (CN) classification requires high-level structural characterizations that are both scale-invariant and computationally efficient. Method

tutorialsarxiv-cs-lg

SignRAG: Unified Retrieval-Augmented Gloss-Free Sign Language Translation

arXiv:2610.11371v1 Announce Type: new Abstract: Contemporary decoder-only large language models (LLMs) have demonstrated strong capabilities across a wide range of domains. However, existing pretraini

Sim-to-Real RL for ASVs using SysID

arXiv:2610.12202v1 Announce Type: new Abstract: Autonomous Surface Vehicles (ASVs) operating in dynamic marine environments require robust control policies for tasks such as path following and station

agentsarxiv-cs-ro

Similarity-as-Evidence: Calibrating Overconfident VLMs for Interpretable and Label-Efficient Medical Active Learning

arXiv:2602.18867v3 Announce Type: replace Abstract: Active Learning (AL) reduces annotation costs in medical imaging by selecting only the most informative samples for labeling, but suffers from cold-

researcharxiv-cs-cv

SimVLA: Zero-Shot Sim-to-Real VLA Learning for Mobile Manipulation

arXiv:2610.11248v1 Announce Type: new Abstract: Large-scale, diverse datasets have driven the success of LLMs and VLMs. But VLAs for robotics remain limited by the cost and complexity of real-world da

safetyarxiv-cs-ro

Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation

arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi

agentsarxiv-cs-ro

SkillWeave: Weaving Heterogeneous Demonstrations into Long-Horizon Manipulation Skills

arXiv:2610.12046v1 Announce Type: new Abstract: Dexterous manipulation requires both large-scale task progression and precise contact-rich interaction, making it challenging to collect demonstrations

safetyarxiv-cs-ro

SLVR: Structured Latent Visual Reasoning via Human-like Reasoning Flows

arXiv:2610.10563v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) often answer visual reasoning questions by relying on linguistic priors rather than task-relevant visual evid

SP-DocReader: Difference-Aware Self-Play for Precise Document OCR

arXiv:2610.11148v1 Announce Type: cross Abstract: Accurate page transcription remains difficult for vision language models under limited input and training budgets. We present SP-DocReader, a self-pla

SpaceCast-Bench: Evaluating Predictive Spatial Reasoning in Vision-Language Models

arXiv:2610.12402v1 Announce Type: cross Abstract: Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input. Yet real-world spatial intel

Applications

SPAN-Nav: Generalized Spatial Awareness for Versatile Embodied Navigation

arXiv:2603.09163v2 Announce Type: replace Abstract: Recent embodied navigation approaches leveraging Vision-Language Models (VLMs) demonstrate strong generalization in versatile Vision-Language Naviga

applicationsarxiv-cs-ro

Sparse Attention Is Matrix Approximation, Not Choosing from a Bag of Values

arXiv:2610.10871v1 Announce Type: new Abstract: Large Language Models (LLMs) achieve strong performance across many domains, but their efficiency is limited by the quadratic cost of attention with res

researcharxiv-cs-cl

SparseDecoding: Decoding-Aware Pruning for Accurate and Efficient LLM Inference

arXiv:2610.12327v1 Announce Type: cross Abstract: The memory-bound nature of the decoding stage of large language model (LLM) inference incurs significant latency. Layer-wise training-free network pru