Search: “framework”

arXiv:2605.28132v1 Announce Type: new Abstract: Spatial intelligence requires visual representations that capture both semantic objects and geometric structure in the physical world. To support this,

tutorialsarxiv-cs-cv

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Whose Is This?: Context-Aware Object Ownership Inference with Uncertainty-Guided Questioning

DGX agent

arXiv:2605.28087v1 Announce Type: new Abstract: Service robots must infer object ownership to correctly interpret instructions such as 'bring me my cup.' However, ownership is a latent attribute that

researcharxiv-cs-ro

28 May 2026

You Are in Control of Your State: Why Human Outcomes Are Controllable Through Causal State Intervention

arXiv:2605.27580v1 Announce Type: new Abstract: A central puzzle for the behavioural sciences and for human-facing artificial intelligence is the persistence of within-person variability. The same ind

applicationsarxiv-cs-ai

You Live More Than Once: Towards Hierarchical Skill Meta-Evolving

arXiv:2605.28390v1 Announce Type: new Abstract: Test-time skill evolving is regarded as a new paradigm for enhancing deployed agentic systems. Existing works mainly focus on hard-coded skill evolving

ZipRL: Adaptive Multi-Turn Context Compression with Hindsight Response Replay

arXiv:2605.28069v1 Announce Type: new Abstract: Adaptive context compression is vital for scaling Large Language Models (LLMs) to complex, multi-turn agent tasks. However, rule-based compression metho

384 people in the Hermes Agent Jam Session in our discord, happening now! Come check out the latest projects people are working on and showi…

Nous Research announced a live Discord event called the Hermes Agent Jam Session with 384 participants, where developers showcased ongoing projects and innovations. The event provided a venue for the

agentsnous-research--x

A Method for Learning Large-Scale Computational Construction Grammars from Semantically Annotated Corpora

arXiv:2603.12754v2 Announce Type: replace Abstract: We present a method for learning large-scale, broad-coverage construction grammars from corpora of language use. Starting from utterances annotated

researcharxiv-cs-cl

A multifractal-based masked auto-encoder: an application to medical images

arXiv:2605.26287v1 Announce Type: new Abstract: Masked autoencoders (MAE) have shown great promise in medical image classification. However, the random masking strategy employed by traditional MAEs ma

researcharxiv-cs-cv

Accountable Human-AI Deliberation with LLMs: Scaling Collective Intelligence through Symbiotic Scaffolding

arXiv:2605.26940v1 Announce Type: new Abstract: Large language models (LLMs) can support democratic deliberation at scales previously constrained by turn-taking and facilitation bandwidth. Recent work

researcharxiv-cs-cl

AD-H: Language-guided Autonomous Driving with Hierarchical Agents

arXiv:2406.03474v2 Announce Type: replace Abstract: Language-guided autonomous driving requires bridging a large abstraction gap between high-level natural-language instructions and low-level vehicle

agentsarxiv-cs-cv

AdaMorph: Unified Motion Retargeting via Embodiment-Aware Adaptive Transformers

arXiv:2601.07284v2 Announce Type: replace Abstract: Retargeting human motion to heterogeneous robots is a fundamental challenge in robotics, primarily due to the severe kinematic and dynamic discrepan

researcharxiv-cs-ro

Adaptation-Free Heterogeneous Collaborative Perception with Unseen Agent Configurations

arXiv:2605.26642v1 Announce Type: new Abstract: Collaborative perception improves 3D object detection by enabling agents to share complementary observations, but most existing methods assume fixed or

agentsarxiv-cs-cv

Advancing Metallic Surface Defect Detection via Anomaly-Guided Pretraining on a Large Industrial Dataset

arXiv:2509.18919v2 Announce Type: replace Abstract: The pretraining-finetuning paradigm is a crucial strategy in metallic surface defect detection for mitigating the challenges posed by data scarcity.

researcharxiv-cs-cv

AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion

arXiv:2605.26130v1 Announce Type: new Abstract: Operational weather prediction at kilometer scales remains computationally prohibitive for traditional numerical weather prediction (NWP) models, limiti

safetyarxiv-cs-lg

AlignEvoSkill: Towards Knowledge-Aware and Task-Aligned Agent Skill Evolution

arXiv:2506.23149v2 Announce Type: replace Abstract: Reusable skills play a key role in improving LLM-based agents, but existing skill-evolution methods often fail to ensure that evolved skills both co

safetyarxiv-cs-cl

Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data Pipelines

arXiv:2605.26442v1 Announce Type: cross Abstract: Much of the alignment tuning literature is organized around optimization objectives, while the construction of alignment data is often treated implici

An End-to-End Learning Approach for Solving Capacitated Location-Routing Problems

arXiv:2511.02525v2 Announce Type: replace-cross Abstract: The capacitated location-routing problems (CLRPs) are classical problems in combinatorial optimization, which require simultaneously making lo

An In-Vitro Study on Cross-Lingual Generalization in Language Models

arXiv:2605.26683v1 Announce Type: cross Abstract: Cross-lingual transfer in language models is difficult to study in natural corpora because lexical overlap, morphology, data imbalance, and tokenizati

researcharxiv-cs-ai

Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model

arXiv:2602.07120v2 Announce Type: replace Abstract: Language models (LMs) tend to memorize portions of their training data and emit verbatim spans. When the underlying sources are sensitive or copyrig

researcharxiv-cs-cl

AnySurf: Any Surface Generation with Directed Edge

arXiv:2605.26149v1 Announce Type: cross Abstract: Open surface components prevail in real industrial 3D content and support rendering, physical simulation and geometric editing. Garments serve as a ty

researcharxiv-cs-cv

APEX: Amplitude Anchors and Phase Priors for Target-Scarce Higher-Frequency Wave Prediction

arXiv:2605.26732v1 Announce Type: new Abstract: Learning-based surrogates have become increasingly effective for wave-field prediction, and neural operators in particular have shown strong performance

researcharxiv-cs-lg

Approximate Equivariance via Projection-based Regularisation

arXiv:2601.05028v2 Announce Type: replace Abstract: Equivariance is a powerful inductive bias in neural networks, improving generalisation and physical consistency. Recently, however, non-equivariant

safetyarxiv-cs-lg

Are Video Models Zero-Shot Learners and Reasoners in Education? EduVideoBench, A Knowledge-Skills-Attitude Benchmark for Educational Video Generation

model-releasesarxiv-cs-cl

arXiv:2605.26918v1 Announce Type: new Abstract: Video generation models (VGMs) are rapidly entering classrooms, yet existing benchmarks evaluate only perceptual quality, intrinsic faithfulness, generi

Assessing Per-Sample Membership Inference Vulnerability without Retraining

arXiv:2602.15919v2 Announce Type: replace-cross Abstract: Recent work in the privacy literature shows that sample-targeted membership inference attacks (MIAs) significantly outperform untargeted appro

researcharxiv-cs-ai

Hardware

AssetGen: Deployable 3D Asset Generation at Interactive Speed

arXiv:2605.26137v1 Announce Type: cross Abstract: While 3D generation is progressing rapidly, recent work has often focused on obtaining high-resolution assets, leaving user experience and deployabili

hardwarearxiv-cs-ai

ATOM: Instantiating Budget-Controllable Multi-Agent Collaboration via Nucleus-Electron Hierarchy

arXiv:2605.26178v1 Announce Type: cross Abstract: Large Language Model (LLM)-based multi-agent systems rely on optimized collaboration topologies to balance performance and communication costs. Howeve

agentsarxiv-cs-lg

Auditing and Fixing Economic Validity in Tabular Foundation Models for Discrete Choice

arXiv:2605.26559v1 Announce Type: cross Abstract: Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks requi

Augment Engineering: A Methodology for Multi-Tool AI Orchestration Across Professional Domains

arXiv:2605.26146v1 Announce Type: cross Abstract: Organizations increasingly deploy separate purpose-built AI tools across professional domains, often hiring domain specialists for each, recreating th

applicationsarxiv-cs-ai

BEAT: Rhythm-Elastic Alignment for Agentic Music-guided Movie Trailer Generation

model-releasesarxiv-cs-cv

arXiv:2605.27067v1 Announce Type: new Abstract: Automatic movie trailer generation must select shots from a full-length film and synchronize them with background music. Existing methods either relegat

Belief-Sim: Towards Belief-Driven Simulation of Demographic Misinformation Susceptibility

arXiv:2603.03585v2 Announce Type: replace-cross Abstract: Misinformation is a growing societal threat, and susceptibility to misinformative claims varies across demographic groups due to differences i

Beyond Binary: Turning Partial Success into Dense Verifiable Rewards for Reinforcement Learning in Code Generation

arXiv:2601.03525v3 Announce Type: replace-cross Abstract: Effective reward design is a central challenge in Reinforcement Learning (RL) for code generation. Mainstream test-suite-level outcome rewards

Beyond Self-Talk: A Communication-Centric Survey of LLM-Based Multi-Agent Systems

arXiv:2502.14321v3 Announce Type: replace-cross Abstract: Large language model-based multi-agent systems have recently gained significant attention due to their potential for complex, collaborative, a

agentsarxiv-cs-cl

Beyond the Data Mesh Illusion: Designing Modern AI-augmented Lakehouses to Bridge the Gap Between Theory and Practice

arXiv:2605.27131v1 Announce Type: cross Abstract: Enterprise data platforms face an enduring tension between domain self-service and holistic governance. The data mesh paradigm proposed decentralized

Tutorials

BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma

arXiv:2605.26376v1 Announce Type: cross Abstract: Hepatocellular carcinoma (HCC) is biologically heterogeneous, shaped by the interplay between hepatic functional reserve and tumor-related oncologic f

tutorialsarxiv-cs-ai

Black-box Membership Inference Attacks on the Pre-training Data of Image-generation Models

arXiv:2605.27020v1 Announce Type: cross Abstract: The rapid advancement of diffusion-based image generation models has raised serious concerns regarding potential copyright and privacy infringements i

BrickAnything: Geometry-Conditioned Buildable Brick Generation with Structure-Aware Tokenization

arXiv:2605.26182v1 Announce Type: new Abstract: Generating physically buildable brick structures from 3D shapes requires more than geometric reconstruction: the output must also satisfy discrete part

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial

arXiv:2605.26577v1 Announce Type: cross Abstract: Learning-based methods for synthesizing controllers have gained popularity due to their high expressiveness and strong empirical performance. However,

Can Broad Biomedical Knowledge be Contextualized into Scenario-Grounded Propositions?

arXiv:2605.27082v1 Announce Type: new Abstract: Biomedical discovery often requires connecting broad biomedical knowledge with specific experimental or clinical data. Background knowledge suggests rel

agentsarxiv-cs-ai

Certified Causal Attribution for Real-Time Attack Forensics in 6G Network Slicing

arXiv:2605.26679v1 Announce Type: cross Abstract: Cross-slice attack attribution in 6G networks requires identifying causal propagation chains through shared infrastructure in under 100 ms. Existing m

applicationsarxiv-cs-ai

Chain Of Thought Compression: A Theoretical Analysis

arXiv:2601.21576v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) has unlocked advanced reasoning abilities of Large Language Models (LLMs) with intermediate steps, yet incurs prohibitive com

CleanSurvival: Automated data preprocessing for time-to-event models using reinforcement learning

model-releasesarxiv-cs-lg

arXiv:2502.03946v5 Announce Type: replace Abstract: Data preprocessing is often paid little attention in machine learning, despite its potentially significant impact on model performance. While automa

Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis

model-releasesarxiv-cs-cv

arXiv:2605.26483v1 Announce Type: new Abstract: Medical video diagnosis involves inferring clinical decisions from dynamic tissue responses throughout examination processes. Existing methods rely on a

CmIVTP: Cross-modal Interaction-based Vessel Trajectory Prediction for Maritime Intelligence

arXiv:2605.26524v1 Announce Type: cross Abstract: Maritime intelligent transportation systems (MITS) are essential for ensuring navigation safety and efficiency in busy waterways. However, accurate ve

CodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning

model-releasesarxiv-cs-cv

arXiv:2605.26967v1 Announce Type: new Abstract: Existing video captioning methods struggle to balance visual fidelity and redundancy: holistic captions are compact but lose fine-grained evidence, wher

Communication Gain and Delay Cost Under Cross-Timestep Delays in Cooperative Multi-Agent Reinforcement Learning

arXiv:2604.03785v2 Announce Type: replace Abstract: Communication is essential for coordination in cooperative multi-agent reinforcement learning under partial observability, yet cross-timestep delays

agentsarxiv-cs-ai

Constrained Meta Reinforcement Learning with Provable Test-Time Safety

arXiv:2601.21845v2 Announce Type: replace Abstract: Meta reinforcement learning (RL) allows agents to leverage experience across a distribution of tasks on which the agent can train at will, enabling

safetyarxiv-cs-lg

ControlLight: Towards Controllable, Consistent, and Generalizable Low-Light Enhancement

arXiv:2605.25569v2 Announce Type: replace Abstract: Existing deep learning-based low-light enhancement methods are typically trained on limited datasets with single enhancement targets, which restrict

applicationsarxiv-cs-cv

Convergence of Spectral Descent for Non-smooth Optimization

arXiv:2605.26977v1 Announce Type: new Abstract: The Muon optimizer has recently demonstrated remarkable empirical success in training large language models. However, the theoretical understanding of i

researcharxiv-cs-lg