Search: “framework”

On the Expressive Power of GNNs to Solve Linear SDPs

arXiv:2604.27786v1 Announce Type: new Abstract: Semidefinite programs (SDPs) are a powerful framework for convex optimization and for constructing strong relaxations of hard combinatorial problems. Ho

Human

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One thing I love about LangChain is how the OSS pieces build on each other You can build robust workflows directly with LangGraph, our orche…

DGX agent

One thing I love about LangChain is how the OSS pieces build on each other You can build robust workflows directly with LangGraph, our orchestration framework. We also use it as the foundation for Dee

agentsharrison-chase--x

1 May 2026

Optimization before Evaluation: Evaluation with Unoptimised Prompts Can be Misleading

arXiv:2604.27637v1 Announce Type: new Abstract: Current Large Language Model (LLM) evaluation frameworks utilize the same static prompt template across all models under evaluation. This differs from t

researcharxiv-cs-ai

Real-World Doctor Agent with Proactive Consultation through Multi-Agent Reinforcement Learning

arXiv:2505.19630v4 Announce Type: replace Abstract: Large language models (LLMs) struggle in real-world clinical consultations. Single-turn consultation systems require patients to describe all sympto

agentsarxiv-cs-cl

Sparse-View 3D Gaussian Splatting in the Wild

arXiv:2604.27422v1 Announce Type: new Abstract: We propose a 3D novel sparse-view synthesis framework for unconstrained real-world scenarios that contain distractors. Unlike existing methods that prim

applicationsarxiv-cs-cv

TranSplat: Instant Object Relighting in Gaussian Splatting via Spherical Harmonic Radiance Transfer

arXiv:2503.22676v5 Announce Type: replace Abstract: We present TranSplat, a method for instant, accurate object relighting within the Gaussian Splatting (GS) framework. Rather than relying on costly i

applicationsarxiv-cs-cv

Why Self-Supervised Encoders Want to Be Normal

arXiv:2604.27743v1 Announce Type: cross Abstract: We develop a geometric and information-theoretic framework for encoder-decoder learning built on the Information Bottleneck (IB) principle. Recasting

researcharxiv-cs-ai

Hardware

AdaFRUGAL: Adaptive Memory-Efficient Training with Dynamic Control

arXiv:2601.11568v2 Announce Type: replace-cross Abstract: Training Large Language Models (LLMs) is highly memory-intensive due to optimizer state overhead. The FRUGAL framework mitigates this with gra

hardwarearxiv-cs-ai

Alter-Art: Exploring Embodied Artistic Creation through a Robot Avatar

arXiv:2604.26473v1 Announce Type: new Abstract: As with every emerging technology, new tools in the hands of artists reshape the nature of artwork creation. Current frameworks for robotics in arts dep

agentsarxiv-cs-ro

Auditing Marketing Budget Allocation with Hindsight Regret

model-releasesarxiv-cs-ai

arXiv:2604.25977v1 Announce Type: cross Abstract: Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized al

Industry

Building gets easier

This article from Ben's Bites likely discusses recent developments or tools that are simplifying the software development or product building process. The piece probably covers new frameworks, platfor

industryben-s-bites

Checkout DeepAgents deploy here: https://docs.langchain.com/oss/python/deepagents/deploy We're shipping updates every week (almost every day…

applicationsharrison-chase--x

LangChain's DeepAgents framework is receiving frequent updates and deployments, with documentation available at their official docs site. The project maintains an active development cycle with updates

Deep Agents is all you need https://github.com/langchain-ai/deepagents

Deep Agents is a framework or library developed by LangChain that enables the creation of sophisticated AI agents with enhanced reasoning capabilities. The project likely provides tools and abstractio

agentsharrison-chase--x

DreamProver: Evolving Transferable Lemma Libraries via a Wake-Sleep Theorem-Proving Agent

arXiv:2604.26311v1 Announce Type: new Abstract: We introduce DreamProver, an agentic framework that leverages a 'wake-sleep' program induction paradigm to discover reusable lemmas for formal theorem p

agentsarxiv-cs-ai

DSIPA: Detecting LLM-Generated Texts via Sentiment-Invariant Patterns Divergence Analysis

model-releasesarxiv-cs-ai

arXiv:2604.26328v1 Announce Type: cross Abstract: The rapid advancement of large language models (LLMs) presents new security challenges, particularly in detecting machine-generated text used for misi

Local Ai

Emergent Coordination in Multi-Agent Language Models

arXiv:2510.05174v4 Announce Type: replace-cross Abstract: When are multi-agent LLM systems merely a collection of individual agents versus an integrated collective with higher-order structure? We intr

local-aiarxiv-cs-ai

Explainable Representation of Finite-Memory Policies for POMDPs using Decision Trees

arXiv:2411.13365v2 Announce Type: replace Abstract: Partially Observable Markov Decision Processes (POMDPs) are a fundamental framework for decision-making under uncertainty and partial observability.

tutorialsarxiv-cs-ai

Featurising Pixels from Dynamic 3D Scenes with Linear In-Context Learners

arXiv:2604.26488v1 Announce Type: new Abstract: One of the most exciting applications of vision models involve pixel-level reasoning. Despite the abundance of vision foundation models, we still lack r

researcharxiv-cs-cv

Hermes Agent v0.12.0 - “The Curator Release”

Hermes Agent v0.12.0, released by Nous Research and titled 'The Curator Release,' represents an update to their Hermes Agent framework. This version likely includes improvements to content curation, f

agentsnous-research--x

LIT-RAGBench: Benchmarking Generator Capabilities of Large Language Models in Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2603.06198v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) is a framework in which a Generator, such as a Large Language Model (LLM), produces answers by retrieving docum

Multiple Additive Neural Networks for Structured and Unstructured Data

arXiv:2604.26888v1 Announce Type: new Abstract: This paper extends and explains the Multiple Additive Neural Networks (MANN) methodology, an enhancement to the traditional Gradient Boosting framework,

Probabilistic data quality assessment for structural monitoring data via outlier-resistant conditional diffusion model

arXiv:2604.26366v1 Announce Type: cross Abstract: Data quality assessment is an essential step that ensures the reliability of the subsequent structural health monitoring (SHM) tasks. This study propo

applicationsarxiv-cs-lg

Quantamination: Dynamic Quantization Leaks Your Data Across the Batch

arXiv:2604.26505v1 Announce Type: cross Abstract: Dynamic quantization emerged as a practical approach to increase the utilization and efficiency of the machine learning serving flow. Unlike static qu

Quantum Feature Selection with Higher-Order Binary Optimization on Trapped-Ion Hardware

model-releasesarxiv-cs-lg

arXiv:2604.26834v1 Announce Type: cross Abstract: We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor

SD2AIL: Adversarial Imitation Learning from Synthetic Demonstrations via Diffusion Models

arXiv:2512.18583v2 Announce Type: replace Abstract: Adversarial Imitation Learning (AIL) is a dominant framework in imitation learning that infers rewards from expert demonstrations to guide policy op

safetyarxiv-cs-lg

Local Ai

SecMate: Multi-Agent Adaptive Cybersecurity Troubleshooting with Tri-Context Personalization

arXiv:2604.26394v1 Announce Type: cross Abstract: Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMat

local-aiarxiv-cs-ai

STAR-Filter: Efficient Convex Free-Space Approximation via Starshaped Set Filtering in Noisy Environments

arXiv:2604.26626v1 Announce Type: new Abstract: Approximating collision-free space is fundamental to robot planning in complex environments. Convex geometric representations, such as polytopes and ell

applicationsarxiv-cs-ro

Unsupervised Graph Modeling for Anomaly Detection in Accounting Subject Relationships

arXiv:2604.26216v1 Announce Type: new Abstract: This paper addresses the problem of anomaly detection in accounting subject association structures, proposing a structured modeling and unsupervised dis

What Google Cloud announced in AI this month

model-releasesgoogle-cloud-ai

Editor’s note: Want to keep up with the latest from Google Cloud? Check back here for a monthly recap of our latest updates, announcements, resources, events, learning opportunities, and more. We host

Tools

AIE is run by agents at this point. full unreleased talk here https://x.com/swyx/status/2047757169765089288

This post discusses how AIE (likely an AI system or framework) has evolved to be primarily operated by autonomous agents rather than direct human control. The tweet links to additional unreleased disc

toolsswyx--x

Beyond Accuracy: Benchmarking Cross-Task Consistency in Unified Multimodal Models

arXiv:2604.25072v1 Announce Type: new Abstract: Unified Multimodal Models (uMMs) aim to support both visual understanding and visual generation within a shared representation. However, existing evalua

safetyarxiv-cs-cv

@ComfyUI https://github.com/NousResearch/hermes-agent/tree/main/skills/creative/comfyui

ComfyUI is a node-based UI framework for composing and executing complex workflows, likely used within the Nous Research Hermes Agent system for creative tasks involving image generation or AI model o

agentsnous-research--x

Data-Driven Hamiltonian Reduction for Superconducting Qubits via Meta-Learning

model-releasesarxiv-cs-lg

arXiv:2604.24912v1 Announce Type: cross Abstract: We introduce HAML (Hamiltonian Adaptation via Meta-Learning), a framework for fast online adaptation of effective Hamiltonian models of superconductin

DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing

arXiv:2604.25477v1 Announce Type: new Abstract: Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance t

tutorialsarxiv-cs-cv

Diffusion Model for Manifold Data: Score Decomposition, Curvature, and Statistical Complexity

arXiv:2603.20645v2 Announce Type: replace Abstract: Diffusion models have become a leading framework in generative modeling, yet their theoretical understanding -- especially for high-dimensional data

tutorialsarxiv-cs-lg

Fractionally Supervised Classification with Maxima Nominated Samples

arXiv:2604.25145v1 Announce Type: cross Abstract: Fractionally supervised classification (FSC) offers a flexible framework for combining labeled and unlabeled data in model-based classification, but e

From Ambiguity to Accuracy: The Transformative Effect of Coreference Resolution on Retrieval-Augmented Generation systems

arXiv:2507.07847v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a crucial framework in natural language processing (NLP), improving factual consistency and redu

researcharxiv-cs-cl

GeoSearch: Augmenting Worldwide Geolocalization with Web-Scale Reverse Image Search and Image Matching

arXiv:2604.25390v1 Announce Type: cross Abstract: Worldwide image geolocalization, which aims to predict the GPS coordinates of any image on Earth, remains challenging due to global visual diversity.

researcharxiv-cs-cv

How Can Reinforcement Learning Achieve Expert-level Placement?

arXiv:2604.25191v1 Announce Type: cross Abstract: Chip placement is a critical step in physical design. While reinforcement learning (RL)-based methods have recently emerged, their training primarily

tutorialsarxiv-cs-lg

Instantaneous Planning, Control and Safety for Navigation in Unknown Underwater Spaces

arXiv:2604.05310v2 Announce Type: replace Abstract: Navigating autonomous underwater vehicles (AUVs) in unknown environments is significantly challenging due to poor visibility, weak signal transmissi

safetyarxiv-cs-ro

Learning-Based Automated Adversarial Red-Teaming for Robustness Evaluation of Large Language Models

arXiv:2512.20677v4 Announce Type: replace-cross Abstract: The increasing deployment of large language models (LLMs) in safety-critical applications raises fundamental challenges in systematically eval

safetyarxiv-cs-cl

Measuring the stability and plasticity of recommender systems

arXiv:2508.03941v3 Announce Type: replace-cross Abstract: The typical offline protocol to evaluate recommendation algorithms is to collect a dataset of user-item interactions and then use a part of th

Most pharma agent pilots never make it to production. We’re partnering with @Axtria to close this gap. Built on LangSmith, Axtria’s pharma-n…

Most pharma agent pilots never make it to production. We’re partnering with @Axtria to close this gap. Built on LangSmith, Axtria’s pharma-native AgentOps framework will give life sciences enterprises

agentsharrison-chase--x

Mutual Forcing: Dual-Mode Self-Evolution for Fast Autoregressive Audio-Video Character Generation

arXiv:2604.25819v1 Announce Type: new Abstract: In this work, we propose Mutual Forcing, a framework for fast autoregressive audio-video generation with long-horizon audio-video synchronization. Our a

researcharxiv-cs-cv

NUBO: A Transparent Python Package for Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2305.06709v4 Announce Type: replace Abstract: NUBO, short for Newcastle University Bayesian Optimisation, is a Bayesian optimization framework for the optimization of expensive-to-evaluate black

PSI-Bench: Towards Clinically Grounded and Interpretable Evaluation of Depression Patient Simulators

model-releasesarxiv-cs-cl

arXiv:2604.25840v1 Announce Type: new Abstract: Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulati

Local Ai

Rethinking Efficiency in Neural Combinatorial Optimization: Batched Preference Optimization with Mamba

arXiv:2602.20730v2 Announce Type: replace Abstract: We study efficiency as a first-class objective in Neural Combinatorial Optimization (NCO) and present ECO, an efficient learning framework that comb

local-aiarxiv-cs-lg

Safe-Support Q-Learning: Learning without Unsafe Exploration

arXiv:2604.25379v1 Announce Type: new Abstract: Ensuring safety during reinforcement learning (RL) training is critical in real-world applications where unsafe exploration can lead to devastating outc

safetyarxiv-cs-lg