Search: “persistence”

SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation

arXiv:2605.08043v1 Announce Type: cross Abstract: While text-to-image models have made strong progress in visual fidelity, faithfully realizing complex visual intents remains challenging because many

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Agents

SCOUT: Closed-Loop in-vivo System for Continuous Methane Concentration Monitoring in Cattle

DGX agent

arXiv:2508.04056v2 Announce Type: replace Abstract: Enteric methane measurement from ruminant livestock faces fundamental trade-offs between accuracy and operational feasibility. Existing methods quan

agentsarxiv-cs-ro

11 May 2026

SR^2-LoRA: Self-Rectifying Inter-layer Relations in Low-Rank Adaptation for Class-Incremental Learning

arXiv:2605.07420v1 Announce Type: cross Abstract: Pre-trained models with parameter-efficient fine-tuning (PEFT) have demonstrated promising potential for class-incremental learning (CIL), yet catastr

Structured Prototype-Guided Adaptation for EEG Foundation Models

arXiv:2602.17251v2 Announce Type: replace Abstract: Electroencephalography (EEG) foundation models (EFMs) have shown strong potential for transferable representation learning, yet their adaptation in

The Context Gathering Decision Process: A POMDP Framework for Agentic Search

arXiv:2605.07042v1 Announce Type: new Abstract: Large Language Model (LLM) agents are deployed in complex environments -- such as massive codebases, enterprise databases, and conversational histories

The Convergence Gap: Instruction-Tuned Language Models Stabilize Later in the Forward Pass

arXiv:2605.07282v1 Announce Type: new Abstract: Final outputs hide when a checkpoint commits to its next-token prediction. We introduce the convergence gap, a model-diffing diagnostic that decodes eac

TopoPrune: Robust Data Pruning via Unified Latent Space Topology

arXiv:2602.02739v2 Announce Type: replace-cross Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geom

researcharxiv-cs-ai

Towards Security-Auditable LLM Agents: A Unified Graph Representation

arXiv:2605.06812v1 Announce Type: new Abstract: LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and mult

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

arXiv:2605.07593v1 Announce Type: new Abstract: Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams,

Applications

TraXion: Rethinking Pre-training Frameworks for Mobility and Beyond

arXiv:2605.06906v1 Announce Type: new Abstract: Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the join

applicationsarxiv-cs-lg

Local Ai

Pi Studio Activity Bookmarklet For Ollama Pi

Pi Studio is an extension for Pi that opens a local two-pane browser workspace for working with prompts, responses, Markdown & LaTeX documents, code files, and other common file types. It includes a l

local-air-ollama

8 May 2026

Adaptive Consensus in LLM Ensembles via Sequential Evidence Accumulation: Automatic Budget Identification and Calibrated Commit Signals

arXiv:2605.04236v1 Announce Type: new Abstract: Large Language Model ensembles improve reasoning accuracy up to a performance boundary; beyond it, additional deliberation degrades accuracy. Static-bud

researcharxiv-cs-lg

Adaptivity Under Realizability Constraints: Comparing In-Context and Agentic Learning

arXiv:2605.04995v1 Announce Type: new Abstract: We compare in-context learning with fixed queries and agentic learning with adaptive queries for uniform approximation of task families. We consider two

agentsarxiv-cs-lg

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

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

Benchmarking LLMs on the Massive Sound Embedding Benchmark (MSEB)

arXiv:2605.04556v1 Announce Type: cross Abstract: The Massive Sound Embedding Benchmark (MSEB) has emerged as a standard for evaluating the functional breadth of audio models. While initial baselines

Can AI Help You Get Over Your Breakup? One Session with a Belief-Reframing Chatbot Shows Sustained Distress Reduction

arXiv:2605.03261v1 Announce Type: cross Abstract: Romantic breakups are among the most common and intense sources of psychological distress. We evaluated *overit*, a single-session AI chatbot that use

researcharxiv-cs-ai

Conflict-Aware Fusion: Mitigating Logic Inertia in Large Language Models via Structured Cognitive Priors

model-releasesarxiv-cs-cl

arXiv:2512.06393v5 Announce Type: replace-cross Abstract: Large language models (LLMs) achieve high accuracy on many reasoning benchmarks but remain brittle under structural perturbations of rule-base

cotomi Act: Learning to Automate Work by Watching You

arXiv:2605.03231v1 Announce Type: new Abstract: What if a browser agent could learn your work simply by watching you do it? We present cotomi Act, a browser-based computer-using agent that combines re

DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation

arXiv:2605.04458v1 Announce Type: new Abstract: Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generat

researcharxiv-cs-cl

Evaluating Semantic Fragility in Text-to-Audio Generation Systems Under Controlled Prompt Perturbations

arXiv:2603.13824v2 Announce Type: replace-cross Abstract: Recent advances in text-to-audio generation enable models to translate natural-language descriptions into diverse musical output. However, the

safetyarxiv-cs-ai

Tutorials

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

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

arXiv:2605.03205v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowled

From Language to Logic: A Theoretical Architecture for VLM-Grounded Safe Navigation

arXiv:2605.04327v1 Announce Type: new Abstract: We propose an architecture for integrating high-level, human-provided safety rules and operator-aligned semantic preferences into autonomous robot navig

safetyarxiv-cs-ro

Applications

Gradient Flow Structure and Quantitative Dynamics of Multi-Head Self-Attention

arXiv:2605.04279v1 Announce Type: new Abstract: Transformer self-attention can be interpreted as a gradient flow on the unit sphere, in which tokens evolve under softmax interaction potentials and ten

applicationsarxiv-cs-lg

KernelBench-X: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

arXiv:2605.04956v1 Announce Type: new Abstract: LLM-based Triton kernel generation has attracted significant interest, yet a fundamental empirical question remains unanswered: where does this capabili

KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanning

model-releasesarxiv-cs-ro

arXiv:2602.04129v2 Announce Type: replace Abstract: Heterogeneous multi-robot systems are increasingly used in long-horizon missions requiring coordinated planning across diverse capabilities. However

New Bigtable in-memory tier for sub-millisecond read latency

In the high-stakes world of digital infrastructure, speed isn't just a metric — it’s currency. At Google Cloud Next ‘26 we announced the Bigtable in-memory tier, a breakthrough for our fully managed c

safetygoogle-cloud-ai

OpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation

arXiv:2601.22725v3 Announce Type: replace Abstract: Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remain

RetentiveKV: State-Space Memory for Uncertainty-Aware Multimodal KV Cache Eviction

arXiv:2605.04075v1 Announce Type: cross Abstract: Multimodal Large Language Models face severe challenges in computational efficiency and memory consumption due to the substantial expansion of the vis

researcharxiv-cs-cl

Revisiting the Travel Planning Capabilities of Large Language Models

arXiv:2605.03308v1 Announce Type: new Abstract: Travel planning serves as a critical task for long-horizon reasoning, exposing significant deficits in LLMs. However, existing benchmarks and evaluation

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

arXiv:2601.08623v2 Announce Type: replace Abstract: Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from

safetyarxiv-cs-cv

Stories like this is why we built E2B. Watching @genspark_ai go from zero to $250M ARR in 12 months on our infrastructure is one of the best…

Stories like this is why we built E2B. Watching @genspark_ai go from zero to 250M ARR in 12 months on our infrastructure is one of the best feelings in this job. Their Super Agent does deep research,

agentsyohei-nakajima--x

The Implicit Curriculum: Learning Dynamics in RL with Verifiable Rewards

arXiv:2602.14872v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has been a main driver of recent breakthroughs in large reasoning models. Yet it remains a mys

researcharxiv-cs-lg

Applications

Topology-Constrained Quantized nnUNet for Efficient and Anatomically Accurate 3D Tooth Segmentation

arXiv:2605.04201v1 Announce Type: new Abstract: We propose a topology-constrained quantized nnUNet framework for efficient and anatomically accurate 3D tooth segmentation, addressing the challenges of

applicationsarxiv-cs-cv

TSCG: Deterministic Tool-Schema Compilation for Agentic LLM Deployments

model-releasesarxiv-cs-cl

arXiv:2605.04107v1 Announce Type: cross Abstract: Production agent frameworks (OpenAI Function Calling, Anthropic Tool Use, MCP) transmit tool schemas as JSON, a format designed for machine parsing, n

A Framework for Exploring and Disentangling Intersectional Bias: A Case Study in Fetal Ultrasound

arXiv:2605.02942v1 Announce Type: cross Abstract: Bias in medical AI is often framed as a problem of representation. However, in image-based tasks such as fetal ultrasound, performance disparities can

Artificial Jagged Intelligence as Uneven Optimization Energy Allocation Capability Concentration, Redistribution, and Optimization Governance

arXiv:2605.01420v1 Announce Type: new Abstract: Artificial Jagged Intelligence (AJI) denotes a recurring pattern in which large learning systems exhibit strong local capabilities while remaining weak

CyberAId: AI-Driven Cybersecurity for Financial Service Providers

arXiv:2605.01892v1 Announce Type: new Abstract: European financial institutions face mounting regulatory pressure while their security operations centres remain constrained not by data or staffing but

DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents

arXiv:2605.01789v1 Announce Type: new Abstract: Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a s

Foundation-Model-Based Agents in Industrial Automation: Purposes, Capabilities, and Open Challenges

arXiv:2605.02592v1 Announce Type: new Abstract: Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision suppor

Local Ai

GISclaw: A Comprehensive Open-Source LLM Agent System for Realistic Multi-Step Geospatial Analysis

arXiv:2603.26845v2 Announce Type: replace-cross Abstract: Most LLM-driven GIS assistants solve narrow single-step tasks tightly coupled to proprietary platforms such as ArcGIS or QGIS, limiting their

local-aiarxiv-cs-ai

Local Ai

HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization

arXiv:2605.03562v1 Announce Type: new Abstract: KV-cache quantizers usually optimize storage-space reconstruction, even though attention reads keys through logits and values through attention-weighted

local-aiarxiv-cs-lg

Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling

arXiv:2605.01566v1 Announce Type: new Abstract: Advances in inference methods have enabled language models to improve their predictions without additional training. These methods often prioritize raw

NORA: A Harness-Engineered Autonomous Research Agent for End-to-End Spatial Data Science

arXiv:2605.02092v1 Announce Type: new Abstract: The automation of scientific research workflows has emerged as a transformative frontier in artificial intelligence, yet existing autonomous research ag

safetyarxiv-cs-ai

Position: Safety and Fairness in Agentic AI Depend on Interaction Topology, Not on Model Scale or Alignment

arXiv:2605.01147v1 Announce Type: new Abstract: As large language models are increasingly deployed as interacting agents in high-stakes decisions, the AI safety community assumes that safety propertie

safetyarxiv-cs-ai

Prediction horizon shapes representations in predictive learning

arXiv:2511.09290v2 Announce Type: replace Abstract: Predictive learning has emerged as a central paradigm for training models across diverse data domains and is increasingly viewed as a foundation for

researcharxiv-cs-lg

Robust Path Tracking for Vehicles via Continuous-Time Residual Learning: An ICODE-MPPI Approach

arXiv:2605.03260v1 Announce Type: new Abstract: Model Predictive Path Integral (MPPI) control is a powerful sampling-based strategy for nonlinear autonomous systems. However, its performance is often

agentsarxiv-cs-ro