Search: “framework”

DIVE: Unlocking Self-Improvement in Frozen Language Models Through Diversity-Driven Skill Evolution

model-releasesarxiv-cs-cl

arXiv:2608.12486v1 Announce Type: new Abstract: Large language models (LLMs) cannot retain post-deployment experience without parameter updates. We introduce DIVE, a diversity-driven framework that en

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Research

Enhancing In-Hospital Mortality Prediction Using Multi-Representational Learning with LLM-Generated Expert Summaries

DGX agent

arXiv:2411.16818v2 Announce Type: replace-cross Abstract: To evaluate a multi-representational framework in which large language model (LLM)-generated expert summaries of intensive care unit (ICU) not

researcharxiv-cs-ai

14 Aug 2026

Fast Iterative Five point Relative Pose Estimation

arXiv:2608.13114v1 Announce Type: new Abstract: Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point

researcharxiv-cs-cv

Jagged Judges: Epistemic Stability Under Silence, Pressure, and Persistence

arXiv:2608.12645v1 Announce Type: new Abstract: LLM judges have become central infrastructure for model evaluations, online grading, and reward modeling. Judges are typically validated by accuracy on

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

arXiv:2508.17905v2 Announce Type: replace Abstract: Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and k

researcharxiv-cs-cl

PseudoMapLabeler: Confidence-Aware Pseudo-Label Generation for Semi-Supervised Online Mapping

arXiv:2608.12600v1 Announce Type: cross Abstract: A critical challenge in deploying online HD map construction systems to real-world scenarios is the scarcity of labeled training data, which limits mo

Regulatory Approval Is Not Enough: Gaps in Trustworthy AI Reporting in FDA-Cleared Medical Devices

arXiv:2608.12360v1 Announce Type: cross Abstract: Background: AI/ML-enabled medical devices are increasingly deployed in healthcare under evolving regulatory frameworks. As these systems become more i

safetyarxiv-cs-lg

Virtual Temperature Sensors in Power Transformers Using Neural Ordinary Differential Equations

model-releasesarxiv-cs-lg

arXiv:2608.13260v1 Announce Type: new Abstract: Accurate modeling and forecasting of power transformer thermal behavior are critical for reliability, asset lifetime, and optimized power system operati

Local Ai

Beyond Detection: Evaluating Defensive LLMs Against AI-Generated Social Engineering in Live Turn-by-Turn Interaction

arXiv:2608.10239v1 Announce Type: new Abstract: Generative AI makes social-engineering attacks more fluent, adaptive, and scalable, increasing the need for LLM-based de- fenders that can protect users

local-aiarxiv-cs-ai

Agents

Co-Evolution in Agentic Systems: Toward Self-Directed Evolution Beyond Human Design

arXiv:2608.10299v1 Announce Type: new Abstract: Agentic systems are increasingly expected to improve after deployment, yet single-entity self-evolution is often bounded by a static learning context, s

agentsarxiv-cs-cl

Exploring Decoupled Spatio-Temporal Consistency Learning and Self-Prompting Evolution for Self-Supervised Tracking

model-releasesarxiv-cs-cv

arXiv:2507.21606v2 Announce Type: replace Abstract: The success of visual tracking has been largely driven by datasets with manual box annotations. However, these box annotations require tremendous hu

GS-CPE: Unified 6-Degree-of-Freedom Camera Pose Estimation via 3D Gaussian Splatting

arXiv:2608.10938v1 Announce Type: new Abstract: Despite substantial progress in visual localization, from scene coordinate regression to direct camera pose regression, achieving both robust generaliza

researcharxiv-cs-cv

Hardware

Hand-Written PTX Tensor-Core GEMM Kernels: A Multi-Precision Study on NVIDIA L4

arXiv:2608.10103v1 Announce Type: cross Abstract: High-performance Tensor Core kernels rely on a low-level PTX pipeline built from asynchronous data movement with cp.async, warp-level matrix loads wit

hardwarearxiv-cs-ai

Leveraging Large Language Models for Causal Discovery: a Constraint-based, Argumentation-driven Approach

arXiv:2602.16481v2 Announce Type: replace Abstract: Causal discovery seeks to uncover causal relations from data, typically represented as causal graphs, and is essential for predicting the effects of

No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding

model-releasesarxiv-cs-cl

arXiv:2503.05061v3 Announce Type: replace Abstract: Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as bus

Reasoning Shortcuts and Value Symmetries: What Symmetry Permits, Architecture Realizes, and Optimization Selects

arXiv:2608.10420v1 Announce Type: new Abstract: Reasoning shortcuts are solutions of a neurosymbolic system's rules that produce correct predictions through unintended concepts. A recent framework of

Tutorials

ReCBM: Uncertainty-Gated Relational Reasoning for Concept Bottleneck Models

arXiv:2608.10004v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide an interpretable framework by grounding predictions in human-understandable concepts, enabling semantic inspect

tutorialsarxiv-cs-ai

Rethinking LLM Verification: Evidence Structure, Uncertainty, and Selective Refinement

model-releasesarxiv-cs-cv

arXiv:2608.10725v1 Announce Type: new Abstract: Large language models (LLMs) often rely on shortcuts rather than systematic reasoning, raising safety concerns in medical applications. Allowing models

An evolutionary model of animats with VLM-based subjective evaluation

arXiv:2608.07537v1 Announce Type: cross Abstract: In this study, we propose a framework that incorporates subjective evaluations provided by a Vision-Language Model (VLM) into the fitness evaluation a

researcharxiv-cs-ai

An invertible generative model for forward and inverse problems

arXiv:2509.03910v2 Announce Type: replace-cross Abstract: We formulate inverse problems in a Bayesian framework and aim to train an invertible generative model that is capable of simulation (i.e., sam

Bridging the Gap Between Semantics and Reconstruction:Unifying Sign Language Translation and Production

arXiv:2608.09045v1 Announce Type: cross Abstract: Recent advances in sign language (SL) research have shown a trend toward unifying multiple sign language understanding (SLU) subtasks, such as isolate

Explore, Map, Remember, Decide: Are Embodied VLMs Ready for Safety-Critical Scenarios?

arXiv:2608.08077v1 Announce Type: new Abstract: Theory of Space framework (ToS) assesses the spatial understanding of curiosity-driven Vision-Language Models (VLMs) under partial observability. As AI

From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch

arXiv:2608.09925v1 Announce Type: cross Abstract: Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of p

LLM-Driven AutoML for Cross-Lingual Handwritten OCR: Closed-Loop Neural Architecture Search with GPT-5, GPT-4o, and Claude Sonnet 4

arXiv:2607.15509v2 Announce Type: replace-cross Abstract: We present a fully automated closed-loop AutoML framework that uses GPT-5, GPT-4o, and Claude Sonnet 4 as autonomous neural architecture desig

Hardware

Real-time physics inversion for retrieval of sub-pixel wildfire temperatures from VSWIR imaging spectroscopy

arXiv:2608.07580v1 Announce Type: new Abstract: In this work, we present a wildfire temperature retrieval framework for VSWIR imaging spectroscopy data, employed on data from NASA's Airborne Visible I

hardwarearxiv-cs-cv

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

arXiv:2608.09512v1 Announce Type: new Abstract: Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and tempo

researcharxiv-cs-ai

Rethinking Learning-Based Influence Maximization: Simple Neural Surrogates and Native Discrete Search

arXiv:2608.08406v1 Announce Type: new Abstract: Existing learning-based influence maximization frameworks rely heavily on complex neural architectures and continuous optimization over seed representat

Agents

Scalable High-Speed Lateral Control for Single-Body and Articulated Autonomous Vehicles

arXiv:2608.08293v1 Announce Type: new Abstract: This paper presents a scalable lateral control framework for robust path tracking of single-body and articulated autonomous vehicles at high speeds. A c

agentsarxiv-cs-ro

AutoMOOSE: An Agentic AI for Autonomous Phase-Field Simulation

arXiv:2603.20986v2 Announce Type: replace Abstract: Phase-field modeling links thermodynamics and kinetics to microstructural evolution, but multiphysics frameworks such as MOOSE require expertise to

Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding

arXiv:2608.06501v1 Announce Type: new Abstract: Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explici

Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection

arXiv:2608.06865v1 Announce Type: cross Abstract: The malicious use of generative artificial intelligence to create highly realistic deepfake videos raises serious ethical concerns and poses substanti

Multi-Level Modeling of Large Language Model Inference Latency and Energy via Hybrid Analytical--Machine-Learning Predictors

arXiv:2608.06723v1 Announce Type: cross Abstract: The rapid scaling of Large Language Models (LLMs) has significantly increased computational cost, energy consumption, and inference latency, making ac

Benchmarking the Benchmarks: Evaluating Benchmarks for Conversational Agents

arXiv:2608.06329v1 Announce Type: cross Abstract: Task-oriented conversational agents are evaluated using curated or automatically generated benchmarks, yet benchmark quality is rarely assessed. Poor

7 Aug 2026

Tutorials

Stochastic Dynamics on Persistence Diagram Space via Reinforcement Learning

arXiv:2608.06276v1 Announce Type: cross Abstract: Persistence diagrams (PDs) provide stable and interpretable summaries of multiscale topological structure. While substantial progress has been made in

tutorialsarxiv-cs-lg

7 Aug 2026

Tree-NET: Enhancing 2D Medical Image Segmentation Through Efficient Low-Level Feature Training

model-releasesarxiv-cs-cv

arXiv:2501.02140v2 Announce Type: replace-cross Abstract: This paper introduces Tree-NET, a novel framework for medical image segmentation that leverages bottleneck supervision to enhance both segment

7 Aug 2026

DASyR-LLM: Domain-Aware Symbolic Regression with LLMs for Kinetic Model Discovery

arXiv:2608.05120v1 Announce Type: new Abstract: Kinetic model discovery is a central challenge in chemical engineering, as accurate rate expressions are essential for understanding and controlling che

From Transparent Labware Segmentation to Collision Avoidance: A Real-Time Edge-Aware Perception Pipeline

model-releasesarxiv-cs-ro

arXiv:2608.04769v1 Announce Type: new Abstract: This paper presents an edge-aware instance segmentation framework that enables real-time robotic collision avoidance with transparent laboratory glasswa

GenAI-Powered Inference

arXiv:2507.03897v3 Announce Type: replace Abstract: We introduce GenAI-Powered Inference (GPI), a statistical framework for both causal and predictive inference using unstructured data, including text

MemFly: On-the-Fly Memory Optimization via Information Bottleneck

arXiv:2602.07885v2 Announce Type: replace Abstract: Long-term memory enables large language model agents to tackle complex tasks through historical interactions. However, existing frameworks encounter

researcharxiv-cs-ai

PRIMAL3: Pathfinding via Reinforcement and Imitation Multi-Agent Learning - Leveraging LaCAM3

arXiv:2608.04905v1 Announce Type: new Abstract: We present PRIMAL3, an ultra-large-scale learning-based framework for multi-agent pathfinding (MAPF) that integrates reinforcement learning, topology-aw

safetyarxiv-cs-ro

SimMOF: AI agent for Automated MOF Simulations

arXiv:2603.29152v2 Announce Type: replace Abstract: Metal-organic frameworks (MOFs) offer a vast design space, and as such, computational simulations play a critical role in predicting their structura

Agents

ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?

arXiv:2608.03874v1 Announce Type: new Abstract: Modern agent frameworks equip large language models with external skill libraries to solve complex tasks. However, it remains unclear whether these syst

agentsarxiv-cs-ai

Explainable AI for the EU Right to Explanation: A Systematic Review of the Law-XAI Translation Gap

arXiv:2608.02699v1 Announce Type: new Abstract: When algorithms make or influence consequential decisions---about loan eligibility, hiring, or healthcare---EU law grants affected individuals a Right t

ISEE: Interactive Semantic Enrichment for Database Fields

arXiv:2608.02604v1 Announce Type: new Abstract: LLM-based agents are increasingly being deployed for data-related tasks, including data sense-making, exploration, and retrieval. However, their perform

Optimising for Flourishing: Flourishing Metrics and Return on Flourishing as Success Criteria for Artificial Intelligence and Post-AGI Economic Systems

arXiv:2608.00151v2 Announce Type: replace-cross Abstract: Current evaluation frameworks for artificial intelligence focus mainly on capability, safety, and proxies such as adoption, engagement, effici

A Large-Scale Multi-Dimensional Empirical Study of LLMs for Conversation Summarization

model-releasesarxiv-cs-cl

arXiv:2606.15974v2 Announce Type: replace Abstract: Despite the significant advancement of LLMs in conversation summarization, their evaluation remains limited by insufficient scenarios, input lengths

4 Aug 2026

Adaptive Human-Robot Collaborative Painting Combining Preference-Based Optimization and Dynamic Motion Primitives

arXiv:2608.01981v1 Announce Type: new Abstract: This work presents a human-centered collaborative framework that integrates Preference-Based Optimization (PBO) and Dynamic Movement Primitives (DMPs) t

researcharxiv-cs-ro

4 Aug 2026

Attention-Steered Vision-Language Models for Sign Language Translation