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arXiv:2508.17077v3 Announce Type: replace-cross Abstract: Current experimental scientists have been increasingly relying on simulation-based inference (SBI) to invert complex non-linear models with in

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Model Releases

Distortion-Resilient Robotic Imitation Learning for Autonomous Cable Routing

DGX agent

arXiv:2606.11577v1 Announce Type: new Abstract: The rapid development of intelligent control methodologies has endowed robots with powerful autonomous intelligence. Cable routing, a ubiquitous foundat

model-releasesarxiv-cs-ro

11 Jun 2026

Doc-to-Atom: Learning to Compile and Compose Memory Atoms

arXiv:2606.12400v1 Announce Type: new Abstract: Long input sequences are central to document understanding and multi-step reasoning in Large Language Models, yet the quadratic cost of attention makes

researcharxiv-cs-cl

Does the Question Really Matter? Training-Free Data Selection for Vision-Language SFT

arXiv:2603.09715v2 Announce Type: replace Abstract: Visual instruction tuning is crucial for improving vision-language large models (VLLMs). However, many samples can be solved via linguistic patterns

researcharxiv-cs-ai

DrivingAgent: Design and Scheduling Agents for Autonomous Driving Systems

arXiv:2606.12236v1 Announce Type: cross Abstract: Many autonomous driving systems are increasingly incorporating foundation models to improve generalization and handle long-tail scenarios. However, th

agentsarxiv-cs-cv

DroneShield-AI: A Multi-Modal Sensor Fusion Framework for Real-Time Autonomous Drone Threat Detection, Behavioral Intent Classification, and Swarm Intelligence in Contested Airspace

arXiv:2606.11687v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified o

Dual-Stance Evaluation of Sycophancy: The Structure of Agreement and the Limits of Intervention

arXiv:2606.11205v1 Announce Type: cross Abstract: Activation steering can shift LLM behaviour, but standard evaluations do not typically test whether a sycophancy-reduction direction also suppresses a

Efficient Multinomial Logistic Bandit via Frequent Directions

arXiv:2606.11968v1 Announce Type: new Abstract: This paper studies efficient online algorithms for multinomial logistic bandits (MLogB), where the feedback distribution over K+1 outcomes follows a mul

Efficient Time Series Clustering from Multiscale Reservoir Dynamics with Granular-Ball Anchoring Graph Optimization

arXiv:2606.12077v1 Announce Type: new Abstract: Time-series clustering remains challenging due to the inherent trade-off between clustering effectiveness and computational efficiency. Similarity-based

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction

arXiv:2606.11909v1 Announce Type: new Abstract: Benchmarks are essential for evaluating embodied spatial intelligence, yet their construction is labor-intensive, hard to reuse, and difficult to mainta

Exploring Adaptive Masked Reconstruction for Self-Supervised Skeleton-Based Action Recognition

arXiv:2606.11450v1 Announce Type: new Abstract: Recently, masked skeleton reconstruction models have emerged as strong action representation learners, driving significant progress in self-supervised s

researcharxiv-cs-cv

Finding Multiple Interpretations in Datasets

arXiv:2606.12277v1 Announce Type: new Abstract: In this paper, we propose an approach to finding sets of similar-performing models (in terms of loss/accuracy measurements) with highly different contex

researcharxiv-cs-lg

Applications

FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI

arXiv:2606.11500v1 Announce Type: cross Abstract: The success of large-scale deep learning models in neuroscience is fundamentally constrained by severe data heterogeneity. Native fMRI data aggregated

applicationsarxiv-cs-lg

Forecasting Future Behavior as a Learning Task

arXiv:2606.11445v1 Announce Type: new Abstract: Trust in an AI system is often anchored by explanations of how it works, which one then uses to forecast its behavior on new inputs. For large reasoning

From Content to Knowledge: Lightning Fast Long-Video Understanding with Neural Knowledge Representations

arXiv:2606.11913v1 Announce Type: new Abstract: We propose a new paradigm for long video understanding by treating a long video as a Neural Knowledge Representation (NKR). NKR represents video content

Frozen Multimodal Embeddings for Personality and Cognitive Ability Assessment in Asynchronous Video Interviews

arXiv:2606.11930v1 Announce Type: cross Abstract: Predicting psychological traits from asynchronous video interviews (AVIs) is a challenging multimodal learning problem because labeled datasets are li

researcharxiv-cs-ai

Goal-Autopilot: A Verifiable Anti-Fabrication Firewall for Unattended Long-Horizon Agents

arXiv:2606.11688v1 Announce Type: cross Abstract: Long-horizon LLM agents are not trusted to run unattended: with no human watching, they confidently report success they never verified. We treat hones

agentsarxiv-cs-ai

GPO: Learning from Critical Steps to Improve LLM Reasoning

arXiv:2509.16456v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in various domains, showing impressive potential on different tasks. Recently, reasoning LLMs hav

GraphInfer-Bench: Benchmarking LLM's Inference Capability on Graphs

model-releasesarxiv-cs-cl

arXiv:2606.11562v1 Announce Type: cross Abstract: Graph analysis underlies many applications whose answers cannot be looked up in a single record or retrieved along a path: laundering rings, drug repu

Holding the FP8 Quality Ceiling at 8-Bit Weights and Activations: INT8 and GGUF Post-Training Quantization of Ideogram 4.0 for Consumer GPUs

arXiv:2606.12280v1 Announce Type: new Abstract: Post-training quantization lets large text-to-image diffusion transformers run on consumer GPUs, yet the hardware-specific trade-offs are seldom measure

IAPO: Input Attribution-Aware Policy Optimization for Tool Use in Small Multimodal Agents

arXiv:2606.11652v1 Announce Type: new Abstract: This paper investigates reinforcement learning (RL) methods for improving tool-calling capabilities in multimodal small language model (SLM) agents. Whi

safetyarxiv-cs-lg

Improving Generalization and Data Efficiency with Diffusion in Offline Multi-agent RL

arXiv:2307.01472v2 Announce Type: replace Abstract: We present a novel Diffusion Offline Multi-agent Model (DOM2) for offline Multi-Agent Reinforcement Learning (MARL). Different from existing algorit

Judging Against the Reference: Uncovering Knowledge-Driven Failures in LLM-Judges on QA Evaluation

arXiv:2601.07506v2 Announce Type: replace Abstract: While large language models (LLMs) are increasingly used as automatic judges for question answering (QA) and other reference-conditioned evaluation

researcharxiv-cs-cl

Tutorials

Learning Patterns and Abstractions from Perceptual Sequences

arXiv:2503.10973v2 Announce Type: replace Abstract: Cognition swiftly breaks high-dimensional sensory streams into familiar parts and uncovers their relations. Why do structures emerge, and how do the

tutorialsarxiv-cs-lg

LibriConvo: Simulating Conversations from Read Literature for ASR and Diarization

model-releasesarxiv-cs-cl

arXiv:2510.23320v2 Announce Type: replace-cross Abstract: We introduce LibriConvo, a synthetic conversational speech corpus for speaker diarization and automatic speech recognition (ASR), built by ins

Measuring Epistemic Resilience of LLMs Under Misleading Medical Context

arXiv:2606.12291v1 Announce Type: new Abstract: Large language models (LLMs) now reach expert-level scores on medical licensing exams, encouraging the assumption that high scores imply safe medical ju

agentsarxiv-cs-cl

MedCTA: A Benchmark for Clinical Tool Agents

arXiv:2606.11702v1 Announce Type: cross Abstract: To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acqui

MemNovo: Look Back at the Spectrum for Balanced De Novo Peptide Sequencing from Mass Spectrometry

arXiv:2606.11868v1 Announce Type: new Abstract: De novo peptide sequencing from tandem mass spectrometry is pivotal in proteomics, enabling identification of novel peptides without reference databases

Metadata-Aware Multi-Prompt Reasoning for Zero-Shot Accident Understanding

arXiv:2606.12047v1 Announce Type: cross Abstract: In this paper, we address the problem of zero-shot understanding of accidents from surveillance videos by identifying when an impact event occurs, wha

Local Ai

MODF-SIR: A Multi-agent Omni-modal Distilled Framework for Social Intelligence Reasoning

arXiv:2606.12018v1 Announce Type: new Abstract: We propose a multi-agent collaborative framework built upon a lightweight Multimodal Large Language Model (MLLM), specifically designed for social intel

local-aiarxiv-cs-ai

Hardware

MPK: A Compiler and Runtime for Mega-Kernelizing Tensor Programs

arXiv:2512.22219v2 Announce Type: replace-cross Abstract: We introduce Mirage Persistent Kernel (MPK), the first compiler and runtime system that automatically transforms multi-GPU model inference int

hardwarearxiv-cs-lg

Multi-Agent Reasoning with Adaptive Worker Allocation for Stance Detection

model-releasesarxiv-cs-cl

arXiv:2606.11609v1 Announce Type: new Abstract: Stance detection requires identifying an author's position toward a target, often from short-form texts where stance is implicit, indirect, or rhetorica

NetBurst: Event-Centric Forecasting of Bursty, Intermittent Time Series

arXiv:2510.22397v2 Announce Type: replace-cross Abstract: Network operators monitor their infrastructure by collecting telemetry data such as packet counts, byte rates, or flow volumes, yet answering

OmniBioTwin: A System-of-Twinned-Systems Framework for Health Digital Twins

arXiv:2606.11264v1 Announce Type: cross Abstract: Health digital twins (HDTs) promise patient-specific modeling and decision support but current approaches remain structurally fragmented: monolithic m

agentsarxiv-cs-ai

Phase Transitions in Attention: A Bayesian Theory of Copy Head Emergence

arXiv:2606.12058v1 Announce Type: cross Abstract: Attention is the key mechanism underlying in-context learning in transformers, and attention patterns have been observed empirically to emerge abruptl

Plan-and-Verify Video Reward Reasoning with Spatio-Temporal Scene Graph Grounding

arXiv:2606.11838v1 Announce Type: new Abstract: Reward models for text-to-video (T2V) generation guide post-training but often fail at fine-grained semantic alignment. We trace this to two structural

safetyarxiv-cs-cv

Precision-Aware Illumination-Disentangled Vision Transformer for Spacecraft 6D Pose Estimation

arXiv:2606.11619v1 Announce Type: new Abstract: Vision sensors provide a lightweight solution for spacecraft proximity operations, but monocular spacecraft 6D pose estimation remains difficult under i

Redesign Mixture-of-Experts Routers with Manifold Power Iteration

arXiv:2606.12397v1 Announce Type: cross Abstract: Router is the cornerstone component to the Mixture-of-Experts models. Serving as expert proxies, the rows of the router matrix compute their similarit

Renewable Lasso without Batch-Number Constraints: A Gradient-Enhanced Approach

arXiv:2606.11738v1 Announce Type: cross Abstract: We study online estimation for high-dimensional generalized linear models with streaming data. First, for the non-distributed setting, we propose a gr

researcharxiv-cs-lg

Restless bandits with imperfect binary feedback: PCL-indexability analysis and computation

arXiv:2606.11192v1 Announce Type: new Abstract: We study restless bandits with binary latent states and imperfect binary feedback, motivated by opportunistic spectrum access with sensing errors. For t

RoVE: Rotary Value Embeddings Attention for Relative Position-dependent Value Pathways

arXiv:2606.11275v1 Announce Type: cross Abstract: Rotary Position Embeddings (RoPE) make attention scores position-relative but leave the value pathway position-blind: the message sent by a value toke

SceneMiner: Identity-Preserving Multi-Task Fine-Tuning for Unified BEV Scene Mining

arXiv:2606.11507v1 Announce Type: new Abstract: Mining hard, safety-critical scenes from driving logs is bottlenecked by the absence of difficulty labels, and no single proxy, collision risk, trajecto

SheafStain: Sheaf-Theoretic Schrodinger Bridge for Spatially and Biologically Coherent Virtual Staining

arXiv:2606.11846v1 Announce Type: new Abstract: Current virtual staining approaches offer the potential for time- and cost-efficient biomarker quantification in cancer diagnostics and prognostics. How

Signed Compression Progress on a Sealed Audit is Goodhart-Resistant

arXiv:2606.11417v1 Announce Type: cross Abstract: Compression progress is a long-standing proposal for intrinsic motivation: reward an agent when its world model becomes better at predicting or compre

Spatially Coupled Phase-to-Depth Calibration for Fringe Projection Profilometry

arXiv:2606.11601v1 Announce Type: new Abstract: In fringe projection profilometry (FPP), depth is commonly recovered by fitting a phase-to-depth relation independently at each camera pixel. Although s

SpikeDecoder: Realizing the GPT Architecture with Spiking Neural Networks

arXiv:2606.12287v1 Announce Type: cross Abstract: The Transformer architecture is widely regarded as the most powerful tool for natural language processing, but due to a high number of complex operati

researcharxiv-cs-ai

Temporal2Seq: A Unified Framework for Temporal Video Understanding Tasks

arXiv:2409.18478v2 Announce Type: replace Abstract: With the development of video understanding, there is a proliferation of tasks for clip-level temporal video analysis, including temporal action det

researcharxiv-cs-cv

The Art of Interrogation: Consistency Amplifies Factuality in Spatial Reasoning

arXiv:2606.11918v1 Announce Type: new Abstract: Current Large Reasoning Models (LRMs) exhibit remarkable general capabilities but significantly underperform in spatial reasoning tasks. Existing approa