Search: “models”

Sketch2Motion: Text-driven 2D Sketch to 3D Animation via Diffusion-guided Skeleton Optimization

arXiv:2605.28394v1 Announce Type: new Abstract: Animation of 2D hand-drawn sketches provides an effective medium for visual communication. However, these sketches pose challenges, particularly in hand

tutorialsarxiv-cs-cv

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Smaller, Younger, and More Impactful: How AI-Assisted Writing Transforms Research Teams

DGX agent

arXiv:2605.27404v1 Announce Type: cross Abstract: The era of Big Science has long been defined by increasingly large and specialized research teams pushing the frontiers of knowledge. However, recent

safetyarxiv-cs-ai

28 May 2026

SmartDirector: Keyframe-Conditioned Cinematic Video Generation with Narrative Pacing Control

arXiv:2605.27891v1 Announce Type: cross Abstract: The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appeal

researcharxiv-cs-ai

SparseOpt: Addressing Normalization-induced Gradient Skew in Sparse Training

arXiv:2605.27541v1 Announce Type: new Abstract: Dynamic Sparse Training (DST) methods train neural networks by maintaining sparsity while dynamically adapting the network topology. Despite the promise

Stabilizing distribution-free probabilistic forecasts

arXiv:2605.28531v1 Announce Type: new Abstract: Multi-step-ahead forecasts are often updated as new observations become available, since shorter forecast horizons typically improve forecast quality. H

Structure over Pixels: Learning Variable-Length Visual Programs

arXiv:2605.27696v1 Announce Type: new Abstract: Discrete visual tokenizers translate images into ordered sequences of codes, providing a natural representation for structural description of scenes. Ye

researcharxiv-cs-cv

Supervised Distributional Reduction via Optimal Transport and Dependence Maximization

arXiv:2605.27619v1 Announce Type: cross Abstract: Learning representations that capture both intrinsic data geometry and target-relevant structure remains a fundamental challenge, particularly in sett

Agents

SynthTools: A Framework for Scaling Synthetic Tools for Agent Development

arXiv:2511.09572v2 Announce Type: replace Abstract: For agentic systems to use external tools to solve complex, long-horizon tasks, we need a large set of diverse and controllable tool-use environment

agentsarxiv-cs-ai

🆕The Age of Async Agents: Devin’s 7x PR growth, 80% AI commits, background agents, memory, testing, & Open-Inspect https://www.latent.space…

🆕The Age of Async Agents: Devin’s 7x PR growth, 80% AI commits, background agents, memory, testing, & Open-Inspect https://www.latent.space/p/cognition @cognition cofounder + CPO @walden_yan and Open-

local-aicognition-ai--x

The Computational Boundary of Inference: Capability Internalization, Training, and the Turing Jump

arXiv:2605.27381v1 Announce Type: cross Abstract: Claims about recursive self-improvement in AI often slide from repeated internal revision to the possibility of qualitatively stronger capability with

researcharxiv-cs-ai

TinyDejaVu: Smaller RAM and Faster Inference with Neural Networks on MCUs for Sensor Data Streams

arXiv:2512.09786v2 Announce Type: replace Abstract: Examples of embedded intelligence include a wide variety of tiny neural networks used on-board wireless sensors and actuators, which are expected to

Token Optimization Strategies for LLM-Based Oracle-to-PostgreSQL Migration

arXiv:2605.28557v1 Announce Type: cross Abstract: LLMs are increasingly used for software modernization, code translation, and database migration. However, LLM-based Oracle2PostgreSQL migration remain

researcharxiv-cs-ai

Toward Robust Semi-supervised Regression via Dual-stream Knowledge Distillation

arXiv:2508.14082v3 Announce Type: replace Abstract: Semi-supervised regression (SSR), which aims to predict continuous scores for samples while reducing the reliance on large-scale labeled data, has r

safetyarxiv-cs-lg

Transformers Provably Learn to Internalize Chain-of-Thought

arXiv:2605.28600v1 Announce Type: new Abstract: Chain-of-Thought (CoT) prompting substantially improves the sample efficiency of transformers, reducing the complexity of tasks like parity learning fro

tutorialsarxiv-cs-lg

Trump loses more control over AI regulation as Illinois passes landmark law

Illinois' House of Representatives passed SB 315, a landmark bill requiring frontier AI companies like OpenAI and Anthropic to create, publish and annually update plans addressing severe or catastroph

safetyars-technica

Trust Region Continual Learning as an Implicit Meta-Learner

arXiv:2602.02417v2 Announce Type: replace Abstract: Continual learning aims to acquire tasks sequentially without catastrophic forgetting, yet standard strategies face a core tradeoff: regularization-

local-aiarxiv-cs-lg

Unification and Optimization of Robust Supervised Learning

arXiv:2605.28165v1 Announce Type: new Abstract: The literature has proposed various robust alternatives to empirical risk minimisation to address failure modes such as distribution shift, label noise

Applications

Unified Multi-Domain Graph Pre-training for Homogeneous and Heterogeneous Graphs via Domain-Specific Expert Encoding

arXiv:2602.13075v2 Announce Type: replace Abstract: Graph pre-training has achieved remarkable success in recent years, delivering transferable representations for downstream adaptation. However, most

applicationsarxiv-cs-lg

Agents

UserHarness: Harnessing User Minds for Stronger Agent Theory-of-Mind

arXiv:2605.27721v1 Announce Type: cross Abstract: Understanding what a user believes and intends is central to building effective agent assistants. This ability is often evaluated through Theory-of-Mi

agentsarxiv-cs-ai

v0.30.0-rc29

Ollama v0.30.0-rc29 is a pre-release version that changes the architecture to directly support llama.cpp instead of building on top of GGML, and adds compatibility with the GGUF file format. MLX is us

local-aiollama-releases

VLM-Based Advanced Rider Assistance System for Motorcycle Safety

arXiv:2605.27948v1 Announce Type: new Abstract: Motorcycles face disproportionately high crash risks compared to cars due to limited protection and heightened sensitivity to surface hazards, yet Advan

safetyarxiv-cs-ro

When Helpful Context Leaks: Privacy Risks in Domain-Adapted ASR

arXiv:2605.28211v1 Announce Type: new Abstract: SpeechLLMs are increasingly deployed in professional settings where domain customisation is standard practice: users supply context in prompts with sens

researcharxiv-cs-cl

Where LLM Annotators Fail: Label-Free Learning on Graphs with LLMs

arXiv:2605.27913v1 Announce Type: new Abstract: Node classification on graphs often requires labeled nodes, yet obtaining labels at graph scale is expensive. When node attributes contain semantic cont

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

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

Zero-shot Quantum Neural Architecture Search

arXiv:2605.27410v1 Announce Type: cross Abstract: Variational Quantum Algorithms (VQAs) are a leading approach to exploiting near-term quantum hardware, leveraging parameterized quantum circuits and c

a16z waking up and realizing we are nowhere near the singularity 🤣

a16z waking up and realizing we are nowhere near the singularity 🤣 OpenAI and Anthropic are effectively telling the market they can't solve every problem with a generic AI coworker. You don't pour bil

safetygary-marcus--x

Adversarial Dual On-Policy Distillation from Expressive Flow-based Teacher

arXiv:2605.27095v1 Announce Type: new Abstract: Learning from demonstrations in embodied control is often cast as behavioral cloning, and recent diffusion or flow-matching policies improve this paradi

safetyarxiv-cs-lg

Agents

Adversarial Training for Robust Coverage Network under Worst-case Facility Losses

arXiv:2605.26763v1 Announce Type: cross Abstract: The Maximal Covering Location-Interdiction Problem (MCLIP) is a classic bi-level optimization problem, which is fundamental to resilient infrastructur

agentsarxiv-cs-ai

AI-Driven Contribution Evaluation and Conflict Resolution: A Framework & Design for Group Workload Investigation

arXiv:2511.07667v2 Announce Type: replace Abstract: The equitable assessment of individual contribution in teams remains a persistent challenge, where conflict and disparity in workload can result in

Tools

ai infra is going VERTICAL

AI infrastructure is shifting toward vertical integration, where companies build specialized, end-to-end solutions optimized for specific use cases rather than relying on generic horizontal platforms.

toolsswyx--x

Tools

[AINews] New AI Infra decacorns: Fireworks, Baseten (with OpenRouter on the way)

Latent Space reports on emerging AI infrastructure companies achieving unicorn status, specifically highlighting Fireworks and Baseten as new decacorns (companies valued at $10+ billion), with OpenRou

toolslatent-space

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

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

Attenuation-Resilient Alternating Optimization for Laparoscopic Liver Landmark Detection

arXiv:2605.26630v1 Announce Type: new Abstract: Liver surface landmark detection is a fundamental prerequisite for anatomical guidance in laparoscopic liver surgery. However, it remains unreliable in

researcharxiv-cs-cv

Applications

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

Automatic Layer Selection for Hallucination Detection

arXiv:2605.26366v1 Announce Type: new Abstract: Recent studies on hallucination detection have shown that hallucination-related signals are more strongly encoded in intermediate layers than in the fin

tutorialsarxiv-cs-ai

b9365

local-aillama-cpp-releases

The search didn't provide specific details about release b9365. Based on the GitHub repository pattern and context, b9365 is a build release of llama.cpp, which is a C/C++ implementation for enabling

b9368

local-aillama-cpp-releases

b9368 is an intermediate build release of llama.cpp, a C/C++ implementation for efficient LLM inference on consumer hardware. The release follows the project's rapid development cycle where multiple b

BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting

arXiv:2605.27044v1 Announce Type: new Abstract: Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critica

local-aiarxiv-cs-ai

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 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

BUILD with Precision: Bottom-Up Inference of Linear DAGs

arXiv:2512.16111v2 Announce Type: replace Abstract: Learning the structure of directed acyclic graphs (DAGs) from observational data is a central problem in causal discovery, statistical signal proces

CART Random Forests as Sequential Allocation over Random Opportunity Sets: A Stochastic-Control Theory of Ensemble Risk

arXiv:2605.26675v1 Announce Type: cross Abstract: CART random forests are among the most widely used modern predictive methods, with well-documented empirical success. Yet, at the mechanistic level, t

local-aiarxiv-cs-lg

Causal Risk Minimization for High-Dimensional Treatments

arXiv:2605.27281v1 Announce Type: new Abstract: Predicting the effect of interventions with many possible variations, e.g., therapeutic content that affects mental health outcomes or an earnings call

tutorialsarxiv-cs-lg

Applications

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

ChainCaps: Composition-Safe Tool-Using Agents via Monotonic Capability Attenuation

arXiv:2605.26542v1 Announce Type: cross Abstract: Tool-using agents increasingly operate in open-ended deployment environments, where they compose file systems, web APIs, code interpreters, and enterp

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

Collaborative Navigation and Exploration with eta-Sparse Gaussian Processes

arXiv:2605.26304v1 Announce Type: new Abstract: Collaborative navigation of heterogeneous robots in unknown environments poses significant challenges due to sensing, communication, and computational l

local-aiarxiv-cs-ro