Search: “framework”

Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting

arXiv:2603.02220v2 Announce Type: replace-cross Abstract: Time series forecasting remains a challenging problem due to the intricate entanglement of intra-period fluctuations and inter-period trends.

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

QuadVerse: An Integrated Framework Aligning Visual-Physical Reality for Quadruped Simulation

DGX agent

arXiv:2606.07118v1 Announce Type: new Abstract: Simulation is central to robot learning, yet the sim-to-real gap remains a major bottleneck.Existing approaches often tackle visual or dynamic gaps sepa

safetyarxiv-cs-ro

8 Jun 2026

ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning

arXiv:2606.06915v1 Announce Type: cross Abstract: Test-time compute (TTC) scaling has emerged as a powerful paradigm for improving large language model (LLM) reasoning by allocating additional compute

VideoSEG-O3: A Multi-turn Reinforcement Learning Framework for Reasoning Video Object Segmentation

model-releasesarxiv-cs-cv

arXiv:2606.06819v1 Announce Type: new Abstract: Reasoning Video Object Segmentation (RVOS) demands a sophisticated integration of temporal dynamics, spatial details, and linguistic reasoning to achiev

What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media

arXiv:2606.06784v1 Announce Type: cross Abstract: Public social media posts can reveal private information through weak cues scattered across text, images, or metadata. Such leakage is often cumulativ

Applications

Binary Gaussian Copula Synthesis: an LLM-powered data augmentation framework for early dialysis prediction in chronic kidney disease

arXiv:2403.00965v2 Announce Type: replace-cross Abstract: Only a small fraction of patients with chronic kidney disease (CKD) progress to dialysis, creating severe class imbalance that limits the perf

applicationsarxiv-cs-ai

Hardware

CuTeGen: An LLM-Based Agentic Framework for Generation and Optimization of High-Performance GPU Kernels using CuTe

arXiv:2604.01489v2 Announce Type: replace-cross Abstract: High-performance GPU kernels are critical to modern machine learning systems, yet developing them remains a manual, expert-driven process. Rec

hardwarearxiv-cs-ai

DAST: A VLM-LLM Framework for Cross-Interface Anomaly Detection in O-RAN

arXiv:2606.06261v1 Announce Type: cross Abstract: O-RAN enables a disaggregated baseband stack with programmable functions that communicate over standardized open interfaces. The same openness that en

From Risk Classification to Action Plan Remediation: A Guardrail Feedback Driven Framework for LLM Agents

arXiv:2606.05805v1 Announce Type: new Abstract: LLM-based guardrails typically safeguard agents by evaluating proposed actions or inputs before execution, producing safety signals such as binary allow

Risk Assessment of Autonomous Driving: Integrating Technical Failures, Ethical Dilemmas, and Policy Frameworks

arXiv:2606.06396v1 Announce Type: new Abstract: Autonomous driving technology has the potential to reduce the large number of road traffic accidents caused by human error each year, but it also brings

SagnacAssisted Enhanced OTDR for Distributed Acoustic Sensing: A Standardized Benchmark and Engineering Evaluation Framework

arXiv:2606.05754v1 Announce Type: cross Abstract: Phase-sensitive optical time-domain reflectometry (phi-OTDR) is widely used in large-scale distributed acoustic sensing (DAS) because it provides dist

A Vision-language Framework for Comparative Reasoning in Radiology

arXiv:2606.06407v1 Announce Type: new Abstract: Medical imaging artificial intelligence has achieved strong performance in isolated image interpretation, but remains poorly aligned with radiological p

researcharxiv-cs-cv

CoT-Space: A Theoretical Framework for Internal Slow-Thinking via Reinforcement Learning

arXiv:2509.04027v3 Announce Type: replace-cross Abstract: Test-time scaling, primarily manifested through multi-step Chain-of-Thought (CoT) reasoning via Reinforcement Learning (RL), has emerged as a

researcharxiv-cs-cl

HomeWorld: A Unified Floorplan-to-Furnished Framework for Generating Controllable, Densely Interactive Whole-Home Scenes

arXiv:2606.06390v1 Announce Type: new Abstract: Indoor scene generation is crucial for robot simulation and modern interior design. However, complex layouts together with scarce 3D scene data make lea

researcharxiv-cs-cv

MARDoc: A Memory-Aware Refinement Agent Framework for Multimodal Long Document QA

arXiv:2606.05749v1 Announce Type: new Abstract: Iterative retrieval-reasoning agents have recently shown promise for multimodal long-document question answering. However, most existing systems maintai

agentsarxiv-cs-cl

MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery

arXiv:2606.06473v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly applied to long-horizon tasks such as scientific discovery and machine learning engineering (MLE),

agentsarxiv-cs-cl

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

ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL

model-releasesarxiv-cs-cl

arXiv:2606.05836v1 Announce Type: new Abstract: Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world d

RAPTOR+: A Visually Grounded Vision-Language Framework to Improve Clinical Trust and Auditability in Automated Cancer Referral Processing

model-releasesarxiv-cs-cv

arXiv:2605.25956v2 Announce Type: replace Abstract: Urgent suspected colorectal cancer (CRC) referrals create operational bottlenecks because semi-structured clinical documents often require manual re

RedditPersona: A Modular Framework for Community-Conditioned LLM Adaptation from Reddit

model-releasesarxiv-cs-cl

arXiv:2606.06027v1 Announce Type: cross Abstract: Community-conditioned language model adaptation requires choices about data collection, community definition, and evaluation that are currently made i

A General Framework for Dynamic Consistent Submodular Maximization

arXiv:2606.04946v1 Announce Type: cross Abstract: Consistency is an important property in dynamic submodular maximization and entails maintaining a near-optimal solution at all times, making only a sm

researcharxiv-cs-lg

AttnRegDeepLab: A Two-Stage Decoupled Framework for Interpretable Embryo Fragmentation Grading

arXiv:2511.18454v3 Announce Type: replace-cross Abstract: Embryo fragmentation is a morphological indicator critical for evaluating developmental potential in In Vitro Fertilization (IVF). However, ma

ChatSOP: An SOP-Guided MCTS Planning Framework for Controllable LLM Dialogue Agents

arXiv:2407.03884v4 Announce Type: replace-cross Abstract: Dialogue agents powered by Large Language Models (LLMs) show superior performance in various tasks. Despite the better user understanding and

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura

Graph-R1: Towards Agentic GraphRAG Framework via End-to-end Reinforcement Learning

arXiv:2507.21892v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucination in LLMs by incorporating external knowledge, but relies on chunk-based retrieval that l

agentsarxiv-cs-cl

Applications

Learning What Not to Impute: An Uncertainty-Aware Diffusion Framework for Meaningful Missingness

arXiv:2606.05073v1 Announce Type: new Abstract: Missing value imputation is a fundamental task in machine learning, with most existing methods assuming that all missing entries correspond to unobserve

applicationsarxiv-cs-lg

Learning While Acting: A Skill-Enhanced Test-Time Co-Evolution Framework for Online Lifelong Learning Agents

arXiv:2606.04815v1 Announce Type: cross Abstract: Lifelong learning is essential for Large Language Model (LLM) agents operating in dynamic, interactive environments. However, existing lifelong learni

MENTOR: A Metacognition-Driven Self-Evolution Framework for Uncovering and Mitigating Implicit Domain Risks in LLMs

arXiv:2511.07107v3 Announce Type: replace Abstract: Ensuring the safety of Large Language Models (LLMs) is critical for real-world deployment. However, current safety measures often fail to address im

Parthenon Law: A Self-Evolving Legal-Agent Framework

arXiv:2606.04602v1 Announce Type: new Abstract: As agents grow more capable, legal-domain LLM agents promise to turn document-heavy matters into reviewable work products -- yet reliable deployment fac

SC-TauPath: A Structural Connectivity Attribution Framework for Mapping Tau Propagation Pathways in Alzheimer's Disease

arXiv:2606.04066v1 Announce Type: cross Abstract: Understanding how structural connections are associated with tau propagation in Alzheimer's disease (AD) remains a central open question, yet existing

researcharxiv-cs-lg

SMADE-IE: Sparse Multi-Agent Framework with Evidence-Driven Debate for Zero-Shot Information Extraction

model-releasesarxiv-cs-cl

arXiv:2606.04691v1 Announce Type: new Abstract: Zero-shot information extraction (IE) with large language models (LLMs) has attracted increasing attention due to its flexibility in adapting to new sch

Toward Autonomous O-RAN: A Multi-Scale Agentic AI Framework for Real-Time Network Control and Management

arXiv:2602.14117v2 Announce Type: replace-cross Abstract: Open Radio Access Networks (O-RAN) promise flexible 6G network access through disaggregated, software-driven components and open interfaces, b

Variance-Gated Ensembles: An Epistemic-Aware Framework for Uncertainty Estimation

arXiv:2602.08142v2 Announce Type: replace Abstract: Machine learning applications require fast and reliable per-sample uncertainty estimation. A common approach is to use predictive distributions from

researcharxiv-cs-lg

A Training-Free Mixture-of-Agents Framework for Multi-Document Summarization using LLMs and Knowledge Graphs

arXiv:2606.03867v1 Announce Type: cross Abstract: Multi-Document Summarization (MDS) plays a critical role in distilling essential information from collections of textual data. Existing approaches oft

AlphaEval: A Comprehensive and Efficient Evaluation Framework for Formula Alpha Mining

arXiv:2508.13174v2 Announce Type: replace Abstract: Formula alpha mining, which generates predictive signals from financial data, is critical for quantitative investment. Although various algorithmic

Build 2026: From observability to ROI for AI agents on any framework

9 min read · June 3, 2026 · Sebastian Kohlmeier Shipping an AI agent is the easy part. Keeping it accurate, safe, and accountable in production is where teams get stuck. Agents are non-deterministic.

agentsmicrosoft-foundry

DMF: A Deterministic Memory Framework for Conversational AI Agents

arXiv:2606.03463v1 Announce Type: new Abstract: Conversational AI agents require memory systems that are both scalable and semantically coherent across long interaction horizons. Existing approaches r

DTKG: Dual-Track Knowledge Graph-Verified Reasoning Framework for Multi-Hop QA

arXiv:2510.16302v2 Announce Type: replace Abstract: Multi-hop reasoning for question answering (QA) plays a critical role in retrieval-augmented generation (RAG) for modern large language models (LLMs

EaDex: A Cross-Embodiment Dexterous Manipulation Framework from Low-Cost Demonstrations

arXiv:2606.03268v1 Announce Type: new Abstract: Dexterous manipulation learning has long been hindered by the high costs of data and training, as pure reinforcement learning typically requires large-s

agentsarxiv-cs-ro

From Control Boundary to Insurance Claim: Reconstructing AI-Mediated Losses Through the CER Framework

arXiv:2606.03777v1 Announce Type: new Abstract: AI losses that arise through an insured organization's generative or agentic AI system require state reconstruction, not merely event reconstruction, be

LEAP: Supercharging LLMs for Formal Mathematics with Agentic Frameworks

arXiv:2606.03303v1 Announce Type: new Abstract: Large Language Models (LLMs) exhibit strong informal mathematical reasoning but struggle to generate mechanically verifiable proofs in formal languages

Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk

arXiv:2308.07867v4 Announce Type: replace-cross Abstract: The absence of formal performance guarantees in machine learning (ML) has limited its adoption for safety-critical power system applications,

safetyarxiv-cs-lg

Learning to Refine: Spectral-Decoupled Iterative Refinement Framework for Precipitation Nowcasting

arXiv:2606.02661v1 Announce Type: cross Abstract: Accurate precipitation nowcasting is vital for disaster mitigation, but deep learning methods face a key trade-off: regression models produce over-smo

LoCAtion: Long-time Collaborative Attention Framework for High Dynamic Range Video Reconstruction

arXiv:2603.14377v2 Announce Type: replace Abstract: Prevailing High Dynamic Range (HDR) video reconstruction methods are fundamentally trapped in a fragile alignment-and-fusion paradigm. While explici

safetyarxiv-cs-cv

MIND: Multi-rationale INtegrated Discriminative Reasoning Framework for Multi-modal Large Models

arXiv:2512.05530v2 Announce Type: replace Abstract: Recently, multimodal large language models (MLLMs) have been widely applied to reasoning tasks. However, they suffer from limited multi-rationale se

SkelHCC: A Hyperbolic CLIP-Driven Cache Adaptation Framework for Skeleton-based One-Shot Action Recognition

arXiv:2606.03610v1 Announce Type: new Abstract: Skeleton-based action recognition aims to understand human behaviors from body joint sequences and is especially challenging in the one-shot setting, wh

safetyarxiv-cs-cv

StepFinder: A Temporal Semantic Framework for Failure Attribution in Multi-Agent Systems

arXiv:2606.03467v1 Announce Type: new Abstract: LLM-based multi-agent systems exhibit remarkable collaborative capabilities in complex multi-step tasks. However, these systems are highly sensitive to

A Framework for Graph-Conditioned Hierarchical Shapley Attribution in Patent Valuation

arXiv:2606.01632v1 Announce Type: cross Abstract: Estimating the economic contribution of a single patent inside a product that embodies tens of thousands of patents is a long-standing unsolved proble