Search: “deployment”

A Systematic Analysis of Biases in Large Language Models

arXiv:2512.15792v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However,

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Activation-Informed Pareto-Guided Low-Rank Compression for Efficient LLM/VLM

DGX agent

arXiv:2510.05544v2 Announce Type: replace Abstract: Large language models (LLM) and vision-language models (VLM) have achieved state-of-the-art performance, but they impose significant memory and comp

researcharxiv-cs-cl

5 Jun 2026

Agents' Last Exam

arXiv:2606.05405v1 Announce Type: cross Abstract: Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deploym

Amortized Nonlinear Model Predictive Control

arXiv:2606.05840v1 Announce Type: cross Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bott

researcharxiv-cs-ro

Asuka-Bench: Benchmarking Code Agents on Underspecified User Intent and Multi-Round Refinement

arXiv:2606.05920v1 Announce Type: cross Abstract: Existing code-generation benchmarks score a single mapping from a complete prompt to a one-shot output. However, real web development is different. Us

b9519

local-aillama-cpp-releases

b9519 is a release build identifier for llama.cpp, an open-source C/C++ project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware . This specif

b9524

local-aillama-cpp-releases

B9524 is a release of llama.cpp, an LLM inference project in C/C++ . This specific build number represents a snapshot from the llama.cpp GitHub releases, which are regularly published to track increme

Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modali…

model-releasesclem-delangue--x

Before the week ends, let's acknowledge one of the most INSANE week ever for open AI, with 25+ notable open-weight drops across every modality: 🧠 LLMs → NVIDIA Nemotron 3 Ultra: 550B hybrid Mamba-MoE,

Beyond Imitation: Reinforcement Learning-Based Sim-Real Co-Training for VLA Models

arXiv:2602.12628v4 Announce Type: replace Abstract: Simulation offers a scalable and low-cost way to enrich vision-language-action (VLA) training, reducing reliance on expensive real-robot demonstrati

safetyarxiv-cs-ro

Beyond tokens: a unified framework for latent communication in LLM-based multi-agent systems

arXiv:2606.05711v1 Announce Type: new Abstract: Multi-agent systems built on large language models (LLMs) have become a prevailing paradigm for tackling complex reasoning, planning, and tool-use tasks

Can We Predict The Human Preference For Text-to-Image Content Prior To Generation And Is It Even Useful To Do So?

arXiv:2606.05478v1 Announce Type: new Abstract: Diffusion Models (DM) have revolutionized text-driven generation by enabling the synthesis of high-quality, photorealistic visual content from user prom

researcharxiv-cs-cv

ChartAttack: Testing the Vulnerability of LLMs to Malicious Prompting in Chart Generation

arXiv:2601.12983v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are increasingly used to automate chart generation from data tables, improving analysis and reporting effic

researcharxiv-cs-cl

CHASE: Adversarial Red-Blue Teaming for Improving LLM Safety using Reinforcement Learning

arXiv:2606.05523v1 Announce Type: new Abstract: Despite advances in safety alignment, prompt-rewriting attacks such as persona modulation, fictional framing and persuasion-based reformulation, can byp

CLEAR: Cognition and Latent Evaluation for Adaptive Routing in End-to-End Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.06219v1 Announce Type: new Abstract: End-to-end autonomous driving models often struggle to balance multi-modal maneuver generation with real-time inference constraints. While diffusion mod

Complexity-Balanced Diffusion Splitting

arXiv:2606.06477v1 Announce Type: new Abstract: Standard continuous-time generative models rely on monolithic architectures that must navigate vastly different signal regimes, from isotropic noise to

local-aiarxiv-cs-cv

Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures

arXiv:2604.03042v2 Announce Type: replace Abstract: Multi-agent autonomous exploration is essential for applications such as environmental monitoring, search and rescue, and industrial-scale surveilla

agentsarxiv-cs-ro

Epistemic Injustice in Language Models: An Audit of Pretraining Filters and Guardrails

arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir

Applications

Ericsson and Snowflake chart an enterprise AI data strategy

Enterprise AI data strategy is separating the organizations that execute on AI from those that aspire to it, and the difference boils down to whether the data foundation was built before the AI was de

applicationssiliconangle

Faithful, Enriched, and Precise: Benchmarking Natural-Science Illustration Generation by T2I models

model-releasesarxiv-cs-cv

arXiv:2606.05949v1 Announce Type: new Abstract: Scientific illustrations are essential tools for communicating research findings, especially in natural science, where they visualize complex concepts a

Hardware

Gotta Grow Fast: Design and Benchmarking of a Tip Mount for High-Speed Vine Robots

arXiv:2606.06040v1 Announce Type: new Abstract: Soft, growing vine robots extend through tip eversion, a mechanism that enables navigation through cluttered environments. However, integrating cameras

hardwarearxiv-cs-ro

Tutorials

How to Stop Shipping Low-Quality RL Environments (with Examples)

This article discusses best practices for ensuring high-quality reinforcement learning (RL) environments, addressing common pitfalls that lead to poor simulation design and implementation. It likely p

tutorialslatent-space

https://ollama.com/library/gemma4/tags

Gemma4 is a language model available through Ollama's model library with multiple tagged versions for different use cases and configurations. The Ollama platform enables users to run open-source large

local-aiollama--x

LadderMan: Learning Humanoid Perceptive Ladder Climbing

arXiv:2606.05873v1 Announce Type: cross Abstract: Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to

safetyarxiv-cs-cv

Learning from Demonstrations over Riemannian Manifolds using Neural ODEs: An Extended Abstract

arXiv:2606.05422v1 Announce Type: new Abstract: Learning from demonstratins (LfD) is usually performed over Euclidean spaces, while the robot state, e.g. orientation, naturally evolves over curved spa

researcharxiv-cs-ro

Measuring the sensitivity of LLM-based structured extraction to prompt, model, and schema choices in clinical discharge summaries

arXiv:2606.05970v1 Announce Type: new Abstract: Large language models are increasingly used for structured extraction from clinical free-text notes, but the sensitivity of their output to upstream con

researcharxiv-cs-cl

Applications

MotionDisco: Motion Discovery for Extreme Humanoid Loco-Manipulation

arXiv:2606.06139v1 Announce Type: new Abstract: We present MotionDisco, a framework that discovers contact-rich, long-horizon humanoid loco-manipulation motions from scratch, without relying on teleop

applicationsarxiv-cs-ro

MS-DKC: A Dataset Knowledge Card Framework for Designing and Adapting Medical Image Segmentation Models

arXiv:2606.06103v1 Announce Type: new Abstract: Medical image segmentation is often framed as a search for stronger architectures, but this can obscure a more fundamental question: what does the datas

researcharxiv-cs-cv

Multilingual Detection of Alzheimer's Disease from Speech: A Cross-Linguistic Transfer Learning Approach

arXiv:2606.05545v1 Announce Type: new Abstract: The development of multilingual Alzheimer's Disease Dementia (AD) detection models presents significant challenges due to the resource-intensive and tim

researcharxiv-cs-cl

OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons

model-releasesarxiv-cs-ro

arXiv:2606.05234v1 Announce Type: new Abstract: Wearable exoskeleton systems hold promise for restoring mobility in individuals with physical impairments, yet most existing controllers rely on static

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation

arXiv:2606.06096v1 Announce Type: cross Abstract: Policy-gradient methods usually optimize expected return, but many real world applications care about distributional properties of returns: tail risk,

PathWISE: Multi-Agent Cancer Pathway Triaging Ontology Learning from Clinical Flowcharts

arXiv:2605.25970v2 Announce Type: replace Abstract: Clinical pathways are disseminated as visual flowcharts where spatial topology, arrow direction, colour coding, and font weight encode critical tria

agentsarxiv-cs-cv

PEFT of SLM for Telecommunications Customer Support: A Comparative Study of LoRA Configurations with Energy Consumption Analysis

arXiv:2606.05176v1 Announce Type: new Abstract: While large language models (LLMs) show strong performance in natural language understanding and generation, their evaluation and adaptation to domain-s

Physics-Guided Deep Unfolding for Blind Cross-Sensor Spectral Super-Resolution via Learning the Spectral Transformation Function

model-releasesarxiv-cs-cv

arXiv:2606.05759v1 Announce Type: new Abstract: Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hyperspectral sensors remain costly and thus unavailable i

Reducing Hallucinations in Complex Question Answering using Simple Graph-based Retrieval-Augmented Generation (long version)

arXiv:2606.05901v1 Announce Type: new Abstract: Large language models (LLMs) have fundamentally transformed the landscape of Natural Language Processing. Despite these advances, LLMs and LLM-based sys

Retrospective Harness Optimization: Improving LLM Agents via Self-Preference over Trajectory Rollouts

arXiv:2606.05922v1 Announce Type: cross Abstract: AI agents rely on a harness of skills, tools, and workflows to solve complex problems. Continually improving this harness is essential for adapting to

agentsarxiv-cs-cl

Robust Scene Transfer for PointGoal Navigation via Privileged Sensor Guided Contrastive Learning

arXiv:2606.05506v1 Announce Type: new Abstract: We propose a sensor-guided adaptive contrastive learning framework for visual representation learning in PointGoal navigation. During training, privileg

safetyarxiv-cs-cv

RoCA: Robust Cross-Domain End-to-End Autonomous Driving

arXiv:2506.10145v3 Announce Type: replace Abstract: End-to-end (E2E) autonomous driving has recently emerged as a new paradigm, offering significant potential. However, few studies have looked into th

agentsarxiv-cs-cv

Safe Embodied AI for Long-horizon Tasks: A Cross-layer Analysis of Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.05660v1 Announce Type: new Abstract: Embodied AI systems are increasingly expected to reason and act over extended horizons in physical environments. This growing capability brings safety t

Tutorials

Sample-efficient Low-level Motion Planning for Robotic Manipulation Tasks via Zero-shot Transfer Learning

arXiv:2606.06041v1 Announce Type: new Abstract: As robotic systems become more sophisticated, the growing complexity of their motion planning models and the longer training times pose substantial chal

tutorialsarxiv-cs-ro

Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars

arXiv:2606.05912v1 Announce Type: new Abstract: Modeling dynamic facial expressions using 3D Gaussian representations remains challenging due to their unstructured nature. Conventional Gaussian avatar

researcharxiv-cs-cv

SkillComposer: Learning to Evolve Agent Skills for Specification and Generalization

arXiv:2606.06079v1 Announce Type: new Abstract: Agent skills, which consist of reusable strategies that guide agent reasoning and action, have shown strong potential for improving model capability at

agentsarxiv-cs-cl

Thousand Token Wood: shipping a multi-agent economy on a 3B model

Thousand Token Wood is a multi-agent economy simulation built on a 3 billion parameter language model, demonstrating how small models can power complex interactive systems with multiple agents. The pr

agentshugging-face

TopoPult-SSL: Gland-Mask-Free Cross-Device Meibomian Gland Segmentation via Self-Distilled Weak Clinical Priors

model-releasesarxiv-cs-cv

arXiv:2606.05347v1 Announce Type: new Abstract: Every new clinical imaging device creates a domain shift where dense gland masks are expensive yet cheap clinical signals -- eyelid outlines, Pult grade

Hardware

Uncertainty-Aware Adaptive Sensor Fusion for Autonomous Navigation

arXiv:2606.05437v1 Announce Type: cross Abstract: This work introduces a hybrid deep learning approach integrated with an Unscented Kalman Filter (UKF) to enhance pose estimation accuracy in Visual-In

hardwarearxiv-cs-cv

Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG

model-releasesgoogle-research

Google's RAG Engine securely connects private enterprise data to LLMs to improve answer accuracy and reduce hallucinations , making it a key component of the Gemini Enterprise Agent Platform for build

Unpaired RGB-Thermal Gaussian-Splatting Using Visual Geometric Transformers

arXiv:2606.05491v1 Announce Type: new Abstract: Multi-modal novel view synthesis (NVS) combining RGB and thermal imagery enables precise 3D scene reconstruction with visual and thermal information. Ho

safetyarxiv-cs-cv

Using Large Language Models to Support High Volume Application Review for an Undergraduate Research Program

arXiv:2606.05564v1 Announce Type: new Abstract: Undergraduate research programs such as the Summer Undergraduate Research Fellowship (SURF) at Purdue University receive thousands of applications every

Value-and-Structure Alignment for Routing-Consistent Quantization of Mixture-of-Experts Models

arXiv:2606.05688v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale foundation models efficiently by activating only a subset of experts for each token, but their large number of exp