Search: “framework”

Human-LLM Collaborative Inductive Coding for Conceptualizing K-12 Educator AI Use

arXiv:2607.28889v1 Announce Type: cross Abstract: Qualitative researchers increasingly encounter interaction corpora whose scale exceeds what manual coding alone can address, and large language models

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Hypergradient-based Bilevel Reinforcement Learning with Improved Sample Complexity

DGX agent

arXiv:2607.28849v1 Announce Type: cross Abstract: Bilevel reinforcement learning (RL) is an important framework within the literature of RL that can be used to formalize various categories of problems

safetyarxiv-cs-ai

3 Aug 2026

Identifying Informative Environments for Cognition Parameter Inference via Bayesian Experimental Design

arXiv:2607.28894v1 Announce Type: new Abstract: Computational cognitive modeling seeks to infer latent cognitive mechanisms underlying observed behavior. Bayesian inverse planning provides a principle

Know It, Act on It: Investigating Memory Utilization in LLM Personalization

arXiv:2607.29433v1 Announce Type: new Abstract: As large language model (LLM) agents evolve into personalized companions, memory has emerged as a core capability. However, LLMs face a knowledge utiliz

agentsarxiv-cs-cl

LAWFUL: Law-Aligned Witness for Faithful Use of Latents

arXiv:2607.28672v1 Announce Type: cross Abstract: When a neural network predicts a physical system accurately, has it learned the governing law as formal, structured knowledge, and if so, does the net

researcharxiv-cs-ai

Metaphor-Induced Algorithmic Steering: Cross-Domain Procedural Transfer in LLM Code Generation

arXiv:2607.28683v1 Announce Type: cross Abstract: Large language models benefit from elements in natural language, such as metaphors and analogies in training data and inference input to achieve gener

researcharxiv-cs-ai

Mirror Learning

arXiv:2607.28737v1 Announce Type: cross Abstract: We investigate imitation learning through the lens of third-person observation and propose a framework for mirror learning: acquiring actionable polic

safetyarxiv-cs-cv

Predicting Steel Fatigue Life from Micrographs Using Physics-Informed Deep Learning

arXiv:2607.28695v1 Announce Type: cross Abstract: Here is the plain text version optimized for arXiv's submission form. Custom macros (like CV and SI) have been converted to standard text/math so they

Provable Diffusion Posterior Sampling for Bayesian Inversion

arXiv:2512.08022v2 Announce Type: replace-cross Abstract: We propose a novel diffusion-based posterior sampling method within a plug-and-play framework. Our approach constructs a probability transport

researcharxiv-cs-lg

RareSense: Rarity-Aware Similarity Search for Anomaly Retrieval in Transactional Data

arXiv:2607.28879v1 Announce Type: cross Abstract: Similarity search over sparse set-valued data is often dominated by frequent background attributes because classical measures such as Jaccard, cosine,

Scaling Scientific Discovery Environments for Turn-Level Agentic RL

arXiv:2607.28990v1 Announce Type: new Abstract: Large language model agents have shown promising capabilities in data-driven scientific discovery tasks, where an agent interacts with an execution envi

Self-Supervised Skill Optimization

arXiv:2607.28777v1 Announce Type: new Abstract: Agent skills provide frozen large language model (LLM) agents with reusable procedural guidance, and recent work shows that such skills can be optimized

agentsarxiv-cs-cl

Sensitivity Analysis of GRU, LSTM and Transformer Encoder in Classification of Automated Driving Systems

arXiv:2607.28665v1 Announce Type: cross Abstract: Automated driving systems (ADSs) are becoming ubiquitous. Future Software Defined Vehicles (SDVs) may be able to run multiple ADSs, both native and af

safetyarxiv-cs-ai

Shaping Scientific Explanations to Expert Perspectives with Persona-Conditioned Reinforcement Learning

arXiv:2603.21846v2 Announce Type: replace Abstract: Explainable AI is increasingly important to scientific discovery. However, existing methods largely ignore that explanation quality is not universal

So-Fake: Benchmarking and Explaining Social Media Image Forgery Detection

model-releasesarxiv-cs-cv

arXiv:2505.18660v5 Announce Type: replace Abstract: Recent advances in AI-powered generative models have enabled the creation of increasingly realistic synthetic images, posing significant risks to in

Towards bridging the gap: Systematic sim-to-real transfer for diverse legged robots

model-releasesarxiv-cs-ro

arXiv:2509.06342v2 Announce Type: replace Abstract: Legged robots must achieve both robust locomotion and energy efficiency to be practical in real-world environments. Yet controllers trained in simul

Uncertainty-Aware Deepfake Detection via Multi-View Structural Learning

arXiv:2607.28769v1 Announce Type: new Abstract: Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution sh

Visual Distribution Anchoring for Efficient Prompt Tuning

arXiv:2607.28967v1 Announce Type: new Abstract: Prompt tuning adapts vision--language models with few trainable parameters, but existing approaches trade off efficiency and adaptation: static textual

Huawei 96gb

Ciao a tutti ho appena comprato 4 Huawei duo 96 GB a poco più di 4mila euro qualcuno ha già utilizzato CANN consigli da darmi? E la prima volta che utilizzo questo framework e non so proprio da dove i

local-air-ollama

1 Aug 2026

A Methodology for Designing Knowledge-Driven Missions for Robots

arXiv:2601.20797v1 Announce Type: cross Abstract: This paper presents a comprehensive methodology for implementing knowledge graphs in ROS 2 systems, aiming to enhance the efficiency and intelligence

Tutorials

AuricularWorld: Hierarchical Action-Guided World Modeling for Fine-Grained Auricular Structure Segmentation from CT Scans

arXiv:2607.28487v1 Announce Type: new Abstract: Fine-grained segmentation of auricular structures in CT is challenging because the ear occupies a small image region, cartilage boundaries are highly ir

tutorialsarxiv-cs-cv

Applications

BladeYOLO: Wind Turbine Blade Defect Detection with Limited Annotations and Weak-Saliency Awareness

arXiv:2607.28065v1 Announce Type: new Abstract: Wind turbine blade defect detection remains highly challenging in real-world inspection scenarios due to limited on-site data and the subtle visual char

applicationsarxiv-cs-cv

Applications

CACHE-UK: A Stability-Aware Memory Editor for Sequentially Updated Quantized LLMs in Finance

arXiv:2607.28292v1 Announce Type: new Abstract: Large Language Models (LLMs) deployed in dynamic financial environments face a critical challenge: maintaining factual accuracy as market conditions, re

applicationsarxiv-cs-cl

Can Vision-Language Models Reason about AI Edits in Images?

arXiv:2607.28464v1 Announce Type: new Abstract: Detection and localization of AI-tampered images are critical for trustworthy AI, yet modern generative models have made such manipulations increasingly

local-aiarxiv-cs-cv

Causal Discovery with Inverted Self-attention for Multivariate Time Series

arXiv:2607.28212v1 Announce Type: new Abstract: Causal discovery in multivariate time series data is challenging due to complex interactions, high dimensionality, and nonlinear dependencies among vari

researcharxiv-cs-cl

Tutorials

CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising

arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving

tutorialsarxiv-cs-cl

Cloud CISO Perspectives: Why AI Threat Defense is the new boardroom baseline

Welcome to the second Cloud CISO Perspectives for July 2026. Today, Chris Betz, CISO, Google Cloud, and Alicja Cade, Senior Director, Office of the CISO, Google Cloud, explain what boards of directors

local-aigoogle-cloud-ai

Applications

Drawing-Recode: Annotation Grounding for Parametric CAD Code Generation from Raster 2D CAD Drawings

arXiv:2607.27558v1 Announce Type: new Abstract: Recovering Parametric CAD sequences from raster-format 2D Computer-Aided Design (CAD) drawings accumulated prior to digital transformation is important

applicationsarxiv-cs-cv

Emulating Cosmic Structure Formation with a Lagrangian Neural Cellular Automaton

arXiv:2607.27320v1 Announce Type: cross Abstract: Field-level inference of cosmological initial conditions from galaxy surveys requires a forward model that is simultaneously accurate in the non-linea

local-aiarxiv-cs-lg

Functional Cache Grafting: Robust and Rapid Code-Policy Synthesis for Embodied Agents

arXiv:2606.13097v2 Announce Type: replace-cross Abstract: Code-writing large language models (CodeLLMs) generate executable code policies for embodied agents by translating natural language goals and

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Hardware

GoGoTB: Agentic RTL Verification with Specification-Grounded Coverage Closure

arXiv:2607.26181v1 Announce Type: new Abstract: Functional verification dominates integrated circuit (IC) front-end engineering effort, and a single missed bug that escapes to silicon can trigger a co

hardwarearxiv-cs-ai

Graph Neural Network Force Fields for Spin Dynamics in Metallic Magnets

model-releasesarxiv-cs-lg

arXiv:2607.28537v1 Announce Type: cross Abstract: Metallic magnets exhibit complex spin dynamics governed by electronically generated interactions. Predictive simulations of such dynamics typically re

IDP AutoOpt: Agent-Driven Optimization of Document Processing Pipeline Configurations

arXiv:2607.26075v1 Announce Type: cross Abstract: We present IDP AutoOpt, an autonomous LLM agent that discovers high-performing configurations for intelligent document processing (IDP) pipelines. Tun

KernelGenBench: A Multi-Source and Multi-Chip Benchmark for LLM-based Kernel Generation

model-releasesarxiv-cs-lg

arXiv:2607.27231v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly increased the demand for efficient accelerator kernels, but kernel development remains a highly specia

LabEvolver: Training-Free Experience Evolution for Safe and Grounded Wet-Lab Agents

arXiv:2607.27690v1 Announce Type: new Abstract: We introduce LabEvolver, a training-free framework that equips safe and grounded wet-lab agents with episodic memory from execution experience. LabEvolv

safetyarxiv-cs-ro

LAST: The Last Query Token Guides Visual Token Pruning for Edge-Cloud Collaborative MLLM Inference

arXiv:2607.27952v1 Announce Type: new Abstract: Multimodal foundation models are reshaping edge-cloud visual intelligence from task-specific feature pipelines into token-based interfaces, where edge d

MatCreatioNN: Machine learning-guided computational discovery of photocatalysts for environmental applications

model-releasesarxiv-cs-lg

arXiv:2607.27295v1 Announce Type: cross Abstract: The rational design of photocatalysts for environmental remediation and CO2 conversion remains limited by the high computational cost and sparse exper

MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memory

arXiv:2607.27834v1 Announce Type: cross Abstract: Persistent memory lets long-running large language model agents reuse information across sessions and tasks. Yet errors in writable memory can persist

agentsarxiv-cs-cl

MeshFM: 2D Features Are All You Need for 3D Shape Understanding

arXiv:2607.27592v1 Announce Type: new Abstract: We present MeshFM, an efficient feedforward framework for extracting rich features from 3D inputs. Our method distills 2D features from visual foundatio

MOON2.0: Dynamic Modality-balanced Multimodal Representation Learning for E-commerce Product Understanding

model-releasesarxiv-cs-cv

arXiv:2511.12449v3 Announce Type: replace Abstract: Recent Multimodal Large Language Models (MLLMs) have significantly advanced e-commerce product understanding. However, they still face three challen

PAC-MAN: Perception-Aware CBF-RL for Whole-Body Safety in Humanoid Dodgeball

model-releasesarxiv-cs-ro

arXiv:2607.28623v1 Announce Type: new Abstract: We present PAC-MAN, a perception-aware CBF-RL framework that couples control-barrier safety with deployment-realistic onboard sensing for whole-body hum

Reasoning Consensus: Structural Ensembling of LLM Reasoning via Weighted DAG Aggregation

arXiv:2607.27783v1 Announce Type: new Abstract: Large Language Models (LLMs) explore problems through chain-of-thought, but this exploration is buried in unstructured prose. On high-stakes tasks, user

researcharxiv-cs-cl

RefCaptioner: Multi-Reference Image-Grounded Video Captioning

model-releasesarxiv-cs-cv

arXiv:2607.28509v1 Announce Type: new Abstract: Existing video captioning models generate natural descriptions of video content but cannot explicitly ground local visual elements to multiple reference

RefineSVG: Visual Feedback-Driven Reinforcement Learning for Image-to-SVG Generation

arXiv:2607.27699v1 Announce Type: new Abstract: We propose RefineSVG, a single-step closed-loop visual feedback framework that enables multimodal large language models (MLLMs) to perform high-fidelity

agentsarxiv-cs-cv

SciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions

arXiv:2607.27955v1 Announce Type: cross Abstract: Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automatio

researcharxiv-cs-cl

SCOPE: Supply-Chain Operations through Coupled Policies for End-to-End Coordination

arXiv:2607.28488v1 Announce Type: cross Abstract: Can supply-chain AI move beyond isolated decision modules toward unified operational planning? A complete replenishment plan specifies which products

safetyarxiv-cs-lg

Secure Aggregation for Privacy-Preserving Federated Learning on Clinical EEG Data

arXiv:2607.28191v1 Announce Type: cross Abstract: Federated learning enables multiple institutions to train shared models without exchanging raw clinical EEG data, but it does not fully prevent privac

local-aiarxiv-cs-lg

smevals - a small eval suite for evaluating models, prompts, and harnesses

model-releasessimon-willison

smevals - a small eval suite for evaluating models, prompts, and harnesses I've been working with Jesse Vincent's Prime Radiant applied AI research lab building out this evals framework to help answer