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Decompose and Recompose: Reasoning New Skills from Existing Abilities for Cross-Task Robotic Manipulation

arXiv:2605.01448v1 Announce Type: cross Abstract: Cross-task generalization is a core challenge in open-world robotic manipulation, and the key lies in extracting transferable manipulation knowledge f

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Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography

DGX agent

arXiv:2605.02245v1 Announce Type: new Abstract: Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep arch

researcharxiv-cs-lg

5 May 2026

Efficient Parameter Estimation of Truncated Boolean Product Distributions

arXiv:2007.02392v3 Announce Type: replace Abstract: We study the problem of estimating the parameters of a Boolean product distribution in d dimensions, when the samples are truncated by a set S subse

EGAD: Entropy-Guided Adaptive Distillation for Token-Level Knowledge Transfer

arXiv:2605.01732v1 Announce Type: new Abstract: Large language models (LLMs) have achieved remarkable performance across diverse domains, yet their enormous computational and memory requirements hinde

tutorialsarxiv-cs-cl

Exploring Accuracy Law for Deep Time Series Forecasters: An Empirical Study

arXiv:2510.02729v2 Announce Type: replace Abstract: Deep time series forecasting has emerged as a rapidly growing field in recent years. Despite the exponential growth of community interests, progress

tutorialsarxiv-cs-lg

Federated Reinforcement Learning for Efficient Mobile Crowdsensing under Incomplete Information

arXiv:2605.02705v1 Announce Type: new Abstract: Mobile crowdsensing (MCS) is a distributed sensing architecture that utilizes existing sensors on mobile units (MUs) to perform sensing tasks. A mobile

FoR-Net: Learning to Focus on Hard Regions for Efficient Semantic Segmentation

arXiv:2605.02764v1 Announce Type: new Abstract: We present FoR-Net, a lightweight architecture for semantic segmentation that focuses on identifying and enhancing hard regions. Instead of relying on h

From Where Things Are to What They Are For: Benchmarking Spatial-Functional Intelligence in Multimodal LLMs

arXiv:2605.02130v1 Announce Type: new Abstract: Human-level agentic intelligence extends beyond low-level geometric perception, evolving from recognizing where things are to understanding what they ar

GameScope: A Multi-Attribute, Multi-Codec Benchmark Dataset for Gaming Video Quality Assessment

arXiv:2605.01272v1 Announce Type: new Abstract: The development of video game streaming has grown rapidly, with major platforms such as YouTube and Twitch using different codecs. To support quality as

I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven …

model-releasesharrison-chase--x

I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven improvement loops Gather data -> Mine Errors -> Find out whi

InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction

model-releasesarxiv-cs-ai

arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i

Logit-Gap Steering: A Forward-Pass Diagnostic for Alignment Robustness

arXiv:2506.24056v2 Announce Type: replace-cross Abstract: RLHF-style alignment trains language models to refuse unsafe requests, but how much operational margin does this refusal rest on? We introduce

safetyarxiv-cs-cl

MSMixer: Learned Multi-Scale Temporal Mixing with Complementary Linear Shortcut for Long-Term Time Series Forecasting

arXiv:2605.02689v1 Announce Type: new Abstract: Long-term time series forecasting requires models that simultaneously capture rapid oscillations, medium-range periodicities, and slowly evolving macro-

Hardware

MusicInfuser: Making Video Diffusion Listen and Dance

arXiv:2503.14505v3 Announce Type: replace Abstract: We introduce MusicInfuser, an approach that aligns pre-trained text-to-video diffusion models to generate high-quality dance videos synchronized wit

hardwarearxiv-cs-cv

Only Say What You Know: Calibration-Aware Generation for Long-Form Factuality

arXiv:2605.01749v1 Announce Type: new Abstract: Large Reasoning Models achieve strong performance on complex tasks but remain prone to hallucinations, particularly in long-form generation where errors

researcharxiv-cs-cl

PRIME: Protein Representation via Physics-Informed Multiscale Equivariant Hierarchies

arXiv:2605.01625v1 Announce Type: new Abstract: Proteins are inherently multiscale physical systems whose functional properties emerge from coordinated structural organization across multiple spatial

Provably Learning Attention with Queries

arXiv:2601.16873v2 Announce Type: replace Abstract: We study the problem of learning Transformer-based sequence models with black-box access to their outputs. In this setting, a learner may adaptively

tutorialsarxiv-cs-lg

RECAP: Transparent Inference-Time Emotion Alignment for Medical Dialogue Systems

arXiv:2509.10746v3 Announce Type: replace Abstract: Large language models in healthcare often produce emotionally flat or opaque responses, failing to provide the transparent reasoning required for cl

safetyarxiv-cs-cl

Local Ai

Robust and Explainable Divide-and-Conquer Learning for Intrusion Detection

arXiv:2605.02015v1 Announce Type: new Abstract: Machine learning-based intrusion detection requires complex models to capture patterns in high-dimensional, noisy, and class-imbalanced raw network traf

local-aiarxiv-cs-lg

SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning

arXiv:2605.01489v1 Announce Type: cross Abstract: Frontier scientific reasoning is rapidly emerging as a key foundation for advancing AI agents in automated scientific discovery. Deep research agents

ScribbleEdit: Synthetic Data for Image Editing with Scribbles and Text

arXiv:2605.01135v1 Announce Type: new Abstract: Recent progress in generative models has significantly advanced image editing capabilities, yet precise and intuitive user control remains difficult. Sp

researcharxiv-cs-cv

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 25+ Sign Languages

arXiv:2605.01720v1 Announce Type: cross Abstract: Existing large-scale sign language resources typically provide supervision only at the level of raw video-text alignment and are often produced in lab

safetyarxiv-cs-cl

Some things never change. If you don’t understand this one, you don’t understand what’s happening AI. Marcus, 1998: neural nets have trouble…

model-releasesgary-marcus--x

Some things never change. If you don’t understand this one, you don’t understand what’s happening AI. Marcus, 1998: neural nets have trouble generalizing far beyond the data. Marcus, 2001, 2012, 2019,

Stable Blanket with Hidden Variables and Cycles

arXiv:2605.01856v1 Announce Type: cross Abstract: Stabilized regression aims to identify a set of predictors whose conditional relationship with a response variable remains invariant across different

STAGE: A Full-Screenplay Benchmark for Reasoning over Evolving Storie

arXiv:2601.08510v3 Announce Type: replace Abstract: Movie screenplays are rich long-form narratives that interleave complex character relationships, temporally ordered events, and dialogue-driven inte

StyleShield: Exposing the Fragility of AIGC Detectors through Continuous Controllable Style Transfer

arXiv:2605.00924v1 Announce Type: new Abstract: AI-generated content (AIGC) detectors are increasingly deployed in high-stakes settings such as academic integrity screening, yet their reliability rest

SURGE: SuperBatch Unified Resource-efficient GPU Encoding for Heterogeneous Partitioned Data

arXiv:2605.01060v1 Announce Type: cross Abstract: We present SURGE, a streaming GPU encoding system deployed in production to generate embeddings for over 800 million texts across 40,000 logical parti

The Company You Keep: How LLMs Respond to Dark Triad Traits

arXiv:2603.04299v3 Announce Type: replace Abstract: Large Language Models (LLMs) often exhibit highly agreeable and reinforcing conversational styles, also known as AI-sycophancy. Although this behavi

researcharxiv-cs-cl

The Compliance Gap: Why AI Systems Promise to Follow Process Instructions but Don't

arXiv:2605.01771v1 Announce Type: new Abstract: An auditor instructs an AI assistant: 'open each file individually using the Read tool -- no scripts, no agents.' The AI replies 'Yes' -- then issues a

The Pragmatic Frames of Spurious Correlations in Machine Learning: Interpreting How and Why They Matter

arXiv:2411.04696v5 Announce Type: replace Abstract: Learning correlations from data forms the foundation of today's machine learning (ML) and artificial intelligence research. While contemporary metho

safetyarxiv-cs-lg

Towards Visual Query Localization in the 3D World

arXiv:2605.01498v1 Announce Type: new Abstract: Visual query localization (VQL) aims to predict the spatio-temporal response of the most recent occurrence in a sequence given a query. Currently, most

TwistNet-2D: Learning Second-Order Channel Interactions via Spiral Twisting for Texture Recognition

arXiv:2602.07262v3 Announce Type: replace Abstract: Second-order feature statistics are central to texture recognition, yet existing mechanisms exhibit a structural tension: bilinear pooling and Gram

Ultrasound Vision-Language Alignment via Contrastive Learning

arXiv:2605.02126v1 Announce Type: new Abstract: Ultrasound foundation models have achieved strong performance on structured prediction tasks but remain exclusively vision-based, limiting zero-shot and

safetyarxiv-cs-cv

Video Generation with Predictive Latents

arXiv:2605.02134v1 Announce Type: new Abstract: Video Variational Autoencoder (VAE) enables latent video generative modeling by mapping the visual world into compact spatiotemporal latent spaces, impr

tutorialsarxiv-cs-cv

ZNO: Stable Rational Neural Operators in the Z-Domain for Discrete-Time Dynamic

arXiv:2605.02356v1 Announce Type: new Abstract: We introduce the Z-Domain Neural Operator (ZNO), a causal neural operator whose layers are stable low-rank multiple-input multiple-output (MIMO) rationa

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts

arXiv:2508.06361v4 Announce Type: replace Abstract: Large Language Models (LLMs) are widely deployed in reasoning, planning, and decision-making tasks, making their trustworthiness critical. A signifi

safetyarxiv-cs-lg

Cascaded Flow Matching for Heterogeneous Tabular Data with Mixed-Type Features

arXiv:2601.22816v2 Announce Type: replace Abstract: Advances in generative modeling have recently been adapted to tabular data containing discrete and continuous features. However, generating mixed-ty

Local Ai

Characterizing the Expressivity of Local Attention in Transformers

arXiv:2605.00768v1 Announce Type: new Abstract: The transformer is the most popular neural architecture for language modeling. The cornerstone of the transformer is its global attention mechanism, whi

local-aiarxiv-cs-cl

Conformalized Quantum DeepONet Ensembles for Scalable Operator Learning with Distribution-Free Uncertainty

arXiv:2605.00330v1 Announce Type: new Abstract: Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but existing approaches face two fundamental limitations: quadr

safetyarxiv-cs-lg

Driving with A Thousand Faces: A Benchmark for Closed-Loop Personalized End-to-End Autonomous Driving

arXiv:2602.18757v2 Announce Type: replace Abstract: Human driving behavior is inherently diverse, yet most end-to-end autonomous driving (E2E-AD) systems learn a single average driving style, neglecti

ExCyTIn-Bench: Evaluating LLM agents on Cyber Threat Investigation

arXiv:2507.14201v3 Announce Type: replace-cross Abstract: We present ExCyTIn-Bench, the first benchmark to Evaluate an LLM agent X on the task of Cyber Threat Investigation through security questions

Faithful Extreme Image Rescaling with Learnable Reversible Transformation and Semantic Priors

arXiv:2605.00605v1 Announce Type: new Abstract: Most recent extreme rescaling methods struggle to preserve semantically consistent structures and produce realistic details, due to the severely ill-pos

FollowTable: A Benchmark for Instruction-Following Table Retrieval

arXiv:2605.00400v1 Announce Type: cross Abstract: Table Retrieval (TR) has traditionally been formulated as an ad-hoc retrieval problem, where relevance is primarily determined by topical semantic sim

Introducing WARM-VR: Benchmark Dataset for Multimodal Wearable Affect Recognition in Virtual Reality

arXiv:2605.00184v1 Announce Type: new Abstract: With the growing integration of human-computer interaction into everyday life, advances in machine learning have enabled systems to better perceive and

Riemannian MeanFlow

arXiv:2602.07744v3 Announce Type: replace Abstract: Diffusion and flow models have become the dominant paradigm for generative modeling on Riemannian manifolds, with successful applications in protein

RTPrune: Reading-Twice Inspired Token Pruning for Efficient DeepSeek-OCR Inference

arXiv:2605.00392v1 Announce Type: new Abstract: DeepSeek-OCR leverages visual-text compression to reduce long-text processing costs and accelerate inference, yet visual tokens remain prone to redundan

Scalable Context-Aware Graph Attention for Unsupervised Anomaly Detection in Large-Scale Mobile Networks

arXiv:2605.00482v1 Announce Type: new Abstract: Mobile network operators must monitor thousands of heterogeneous network elements across the radio access network and the packet core, each exposing hig

SCAN: Structured Capability Assessment and Navigation for LLMs

arXiv:2505.06698v4 Announce Type: replace Abstract: Evaluating Large Language Models (LLMs) has become increasingly important, with automatic evaluation benchmarks gaining prominence as alternatives t

researcharxiv-cs-cl