Search: “models”

Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Framework

arXiv:2605.05055v1 Announce Type: new Abstract: Localization in 5G and 6G networks is essential for important use cases such as intelligent transportation, smart factories, and smart cities. Although

local-aiarxiv-cs-lg

Human

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Research

Adaptive Reorganization of Neural Pathways for Continual Learning with Spiking Neural Networks

DGX agent

arXiv:2309.09550v4 Announce Type: replace-cross Abstract: The human brain can self-organize rich and diverse sparse neural pathways to incrementally master hundreds of cognitive tasks. However, most e

researcharxiv-cs-ai

7 May 2026

Advancing Analytic Class-Incremental Learning through Vision-Language Calibration

arXiv:2602.13670v2 Announce Type: replace Abstract: Class-incremental learning (CIL) with pre-trained models (PTMs) faces a critical trade-off between efficient adaptation and long-term stability. Whi

Anatomy of a failure: When, how, and why deep vision fails in scientific domains

arXiv:2605.04231v1 Announce Type: new Abstract: Mirroring its ubiquity in popular media and all human activities, the use of deep learning (DL) is rapidly growing in scientific imaging modalities. How

safetyarxiv-cs-cv

新しいリアルタイム翻訳モデルを発表できることをうれしく思います。ぜひ本日よりAPIでお試しください。

Yohei Nakajima announced the release of a new real-time translation model and invited users to test it via API starting immediately. The announcement was made on X (formerly Twitter), suggesting this

agentsyohei-nakajima--x

ARISE: A Repository-level Graph Representation and Toolset for Agentic Fault Localization and Program Repair

arXiv:2605.03117v1 Announce Type: cross Abstract: Repository-level fault localization (FL) and automated program repair (APR) require an agent to identify the relevant code units across files, follow

local-aiarxiv-cs-ai

b9055

local-aillama-cpp-releases

B9055 is the latest version of llama.cpp, released on May 7, 2026. Llama.cpp is an LLM inference framework implemented in C/C++ that enables efficient large language model execution with broad hardwar

b9056

local-aillama-cpp-releases

b9056 is a release of llama.cpp, a C/C++ implementation for LLM inference . The project enables users to run LLaMA models on consumer hardware without expensive GPUs or cloud infrastructure . This rel

b9063

local-aillama-cpp-releases

Release b9063 is a build of llama.cpp, a project for LLM inference in C/C++. llama.cpp enables efficient large language model execution on consumer hardware through optimized implementations and quant

Beyond Variance: Prompt-Efficient RLVR via Rare-Event Amplification and Bidirectional Pairing

arXiv:2602.03452v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) is effective for training large language models on deterministic outcome reasoning tasks. Prio

Hardware

Budget-aware Auto Optimizer Configurator

arXiv:2605.04711v1 Announce Type: cross Abstract: Optimizer states occupy massive GPU memory in large-scale model training. However, gradients in different network blocks exhibit distinct behaviors, s

hardwarearxiv-cs-lg

Copula-Based Endogeneity Correction for Doubly Robust Estimation of Treatment Effect

arXiv:2605.03278v2 Announce Type: cross Abstract: Doubly Robust (DR) estimation of treatment effect relies on an untestable assumption that is the absence of unobserved confounding. This assumption is

safetyarxiv-cs-ai

Data-dependent Exploration for Online Reinforcement Learning from Human Feedback

arXiv:2605.04477v1 Announce Type: new Abstract: Online reinforcement learning from human feedback (RLHF) has emerged as a promising paradigm for aligning large language models (LLMs) by continuously c

Demystifying Manifold Constraints in LLM Pre-training

arXiv:2605.04418v1 Announce Type: new Abstract: The empirical success of large language model (LLM) pre-training relies heavily on heuristic stabilization techniques, such as explicit normalization la

Designing a double deep reinforcement learning selection tool for resilient demand prediction

arXiv:2605.04068v1 Announce Type: new Abstract: The use of artificial intelligence in supply chain forecasting has attracted many scientific studies for several decades. However, the process of select

agentsarxiv-cs-lg

Dynamic Hyperparameter Importance for Efficient Multi-Objective Optimization

arXiv:2601.03166v2 Announce Type: replace Abstract: Choosing a suitable ML model is a complex task that can depend on several objectives, e.g., accuracy, fairness, or energy consumption. In practice,

Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators

arXiv:2605.04164v1 Announce Type: new Abstract: Wildfires are a major producer of fine particulate matter, impacting human health and the electrical grid. Accurately forecasting smoke impacts over lon

Applications

Enterprise AI deployment is creating a security blind spot traditional architectures can’t handle

Enterprise AI deployment has fundamentally expanded the cybersecurity attack surface, turning data pipelines, model training environments, identity management systems and supply chains into prime targ

applicationssiliconangle

Evaluating Patient Safety Risks in Generative AI: Development and Validation of a FMECA Framework for Generated Clinical Content

arXiv:2605.04085v1 Announce Type: cross Abstract: Objectives: Large language models (LLMs) are increasingly used for clinical text summarization, yet structured methods to assess associated patient sa

Example-Based Object Detection

arXiv:2605.04501v1 Announce Type: new Abstract: In recent years, object detection has achieved significant progress, especially in the field of open-vocabulary object detection. Unlike traditional met

tutorialsarxiv-cs-cv

Federated Learning for Early Prediction of EV Charging Demand

arXiv:2605.04993v1 Announce Type: new Abstract: Accurate forecasting of electric vehicle (EV) charging demand is critical for grid stability, infrastructure planning, and real-time charging optimizati

France or Spain or Germany or France: A Neural Account of Non-Redundant Redundant Disjunctions

arXiv:2602.23547v2 Announce Type: replace Abstract: Sentences like 'She will go to France or Spain, or perhaps to Germany or France.' appear formally redundant, yet become acceptable in contexts such

tutorialsarxiv-cs-cl

Geometric Entropy and Retrieval Phase Transitions in Continuous Thermal Dense Associative Memory

arXiv:2604.07401v2 Announce Type: replace-cross Abstract: We study the thermodynamic memory capacity of modern Hopfield networks (Dense Associative Memory models) with continuous states under geometri

Tools

@GoogleDeepMind Full demo vidoe: https://youtu.be/WPoy5O81T6s

This post from Pinecone references a full demonstration video from Google DeepMind, likely showcasing a new AI model, research breakthrough, or technical capability developed by DeepMind. The video li

toolspinecone--x

Graph-Augmented LLMs for Swiss MP Ideology Prediction

arXiv:2605.04643v1 Announce Type: new Abstract: Approximating the ideological position of Members of Parliament (MPs) is a fundamental task in political science, helping researchers understand legisla

GTF: Omnidirectional EPI Transformer for Light Field Super-Resolution

arXiv:2605.04581v1 Announce Type: new Abstract: Light field (LF) image super-resolution benefits from Epipolar Plane Images (EPIs), whose line slopes explicitly encode disparity. However, existing Tra

researcharxiv-cs-cv

Harnessing Linguistic Dissimilarity for Language Generalization on Unseen Low-Resource Varieties

arXiv:2605.04500v1 Announce Type: new Abstract: Low-resource language varieties used by specific groups remain neglected in the development of Multilingual Language Models. A great deal of cross-lingu

researcharxiv-cs-cl

HistoMet: A Pan-Cancer Deep Learning Framework for Prognostic Prediction of Metastatic Progression and Site Tropism from Primary Tumor Histopathology

arXiv:2602.07608v2 Announce Type: replace Abstract: Metastatic Progression remains the leading cause of cancer-related mortality, yet predicting whether a primary tumor will metastasize and where it w

tutorialsarxiv-cs-cv

Hybrid Congestion Classification Framework Using Flow-Guided Attention and Empirical Mode Decomposition

arXiv:2605.04752v1 Announce Type: new Abstract: Accurate traffic congestion classification requires models that jointly capture roadway scene context and non-stationary traffic motion, yet most prior

safetyarxiv-cs-cv

Intelligent Knowledge Mining Framework: Bridging AI Analysis and Trustworthy Preservation

arXiv:2512.17795v2 Announce Type: replace-cross Abstract: The unprecedented proliferation of digital data presents significant challenges in access, integration, and value creation across all data-int

researcharxiv-cs-ai

Industry

It's a bit rare for me to agree with @hlntnr, @_NathanCalvin, AND @AdamThierer on something. But we all agree that government FDA-style pre-…

It's a bit rare for me to agree with @hlntnr, @_NathanCalvin, AND @AdamThierer on something. But we all agree that government FDA-style pre-approval for AI models is a bad idea. Check out this great a

industryclem-delangue--x

Learn how to structure your AI stack. Our co-founder @the_bunny_chen talks with @theinfrapod's @tnachen and @ianlivingstone about inference …

Learn how to structure your AI stack. Our co-founder @the_bunny_chen talks with @theinfrapod's @tnachen and @ianlivingstone about inference optimization, the open vs. closed model debate, and building

tutorialsfireworks-ai--x

Learning Correct Behavior from Examples: Validating Sequential Execution in Autonomous Agents

arXiv:2605.03159v1 Announce Type: new Abstract: As autonomous agents become increasingly sophisticated, validating their sequential behavior presents a significant challenge. Traditional testing appro

agentsarxiv-cs-ai

LLM-Based Human-Agent Collaboration and Interaction Systems: A Survey

arXiv:2505.00753v5 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have sparked growing interest in building fully autonomous agents. However, fully autonomous LLM-bas

LLMs Uncertainty Quantification via Adaptive Conformal Semantic Entropy

arXiv:2605.04295v1 Announce Type: new Abstract: LLMs' overconfidence, particularly when hallucinating, poses a significant challenge for the deployment of the models in safety-critical settings and ma

Manifold Steering Reveals the Shared Geometry of Neural Network Representation and Behavior

arXiv:2605.05115v1 Announce Type: new Abstract: Neural representations carry rich geometric structure; but does that structure causally shape behavior? To address this question, we intervene along pat

MedFabric and EtHER: A Data-Centric Framework for Word-Level Fabrication Generation and Detection in Medical LLMs

arXiv:2605.04180v1 Announce Type: new Abstract: Large Language Models exhibit strong reasoning and semantic understanding capabilities but often hallucinate in domains that require expert knowledge, a

Applications

MIRAGE: Retrieval and Generation of Multimodal Images and Texts for Medical Education

arXiv:2605.04772v1 Announce Type: new Abstract: Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related field

applicationsarxiv-cs-cv

MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology

arXiv:2602.02282v2 Announce Type: replace Abstract: Inferring spatial transcriptomics (ST) from histology enables scalable histogenomic profiling, yet current methods are largely restricted to single-

Multi angle Lora for flux Klein

local-air-stablediffusion

A LoRA adapter for FLUX.2 Klein that enables camera angle control across 72 unique positions using 8 azimuths, 9 elevations, and 3 distances . The model rotates objects through 360° azimuth and 60° el

NSL-MT: Linguistically Informed Negative Samples for Efficient Machine Translation in Low-Resource Languages

arXiv:2511.09537v2 Announce Type: replace Abstract: We introduce negative space learning machine translation (NSL-MT), a training method for underresourced languages, that augments limited parallel da

one of the features i'm most excited about in our upcoming langgraph release is delta channels! the langgraph runtime lets you 'checkpoint' …

one of the features i'm most excited about in our upcoming langgraph release is delta channels! the langgraph runtime lets you 'checkpoint' agent progress at every step (model call, tool call, hooks).

agentsharrison-chase--x

Online Nonstochastic Prediction: Logarithmic Regret via Predictive Online Least Squares

arXiv:2605.04364v1 Announce Type: new Abstract: We study online prediction for marginally stable, partially observed linear dynamical systems under nonstochastic disturbances. Our objective is to mini

Order-based Rehearsal Learning

arXiv:2605.04955v1 Announce Type: new Abstract: When a machine learning (ML) model forecasts an undesired event, one often seeks a decision to avoid it, known as the avoiding undesired future (AUF) pr

tutorialsarxiv-cs-lg

Order Matters: Improving Domain Adaptation by Reordering Data

arXiv:2605.05084v1 Announce Type: new Abstract: Domain shift remains a key challenge in deploying machine learning models to the real world. Unsupervised domain adaptation (UDA) aims to address this b

Pact: A Choreographic Language for Agentic Ecosystems

arXiv:2605.03143v1 Announce Type: cross Abstract: Recent advances in large language models have led to the rise of software systems (i.e. agents) that execute with increasing autonomy on behalf of use

agentsarxiv-cs-ai

Physiologically Grounded Driver Behavior Classification: SHAP-Driven Elite Feature Selection and Hybrid Gradient Boosting for Multimodal Physiological Signals

arXiv:2605.05120v1 Announce Type: new Abstract: An interpretable and scalable framework for decoding driving behaviors from multimodal physiological signals is proposed in this study. We utilize multi

ProMediate: A Socio-cognitive framework for evaluating proactive agents in multi-party negotiation

arXiv:2510.25224v3 Announce Type: replace Abstract: While Large Language Models (LLMs) are increasingly used in agentic frameworks to assist individual users, there is a growing need for agents that c

agentsarxiv-cs-cl