Search: “models”

A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation

arXiv:2605.17278v1 Announce Type: new Abstract: Abstract reasoning ability reflects the intelligence and generalization capacity of LLMs to extract and apply abstract rules. However, accurately measur

Research

ACIL: Auto Chain of Thoughts for In-Context Learning

DGX agent

arXiv:2605.17088v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have shown that Chain-of-Thought (CoT) reasoning can substantially improve performance on complex reason

researcharxiv-cs-cl

19 May 2026

Applications

Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning

arXiv:2605.17234v1 Announce Type: new Abstract: Predicting model performance at larger scales enables the design of training strategies and architectures tailored to specific performance targets. Empi

applicationsarxiv-cs-lg

ADR: An Agentic Detection System for Enterprise Agentic AI Security

arXiv:2605.17380v1 Announce Type: new Abstract: We present the Agentic AI Detection and Response (ADR) system, the first large-scale, production-proven enterprise framework for securing AI agents oper

Agentic AI Governance and Lifecycle Management in Healthcare

arXiv:2601.15630v2 Announce Type: replace Abstract: Healthcare organizations are beginning to embed agentic AI into routine workflows, including clinical documentation support and early-warning monito

Algebraic Priors for Approximately Equivariant Networks

arXiv:2506.08244v2 Announce Type: replace-cross Abstract: Equivariant neural networks incorporate symmetries through group actions, embedding them as an inductive bias to improve performance. Existing

Aligned Training: A Parameter-Free Method to Improve Feature Quality and Stability of Sparse Autoencoders (SAE)

arXiv:2605.18629v1 Announce Type: new Abstract: Sparse autoencoders (SAEs) are one of the main methods to interpret the inner workings of deep neural networks (DNNs), decomposing activations into high

AMO: Adaptive Muon Orthogonalization

arXiv:2605.17806v1 Announce Type: new Abstract: Muon has recently emerged as a competitive alternative to AdamW for large-scale pre-training, with orthogonalization via Newton-Schulz (NS) iterations a

Anthropic Claude is now a partner node in ComfyUI Drop Claude into any workflow to: → rewrite weak prompts into great ones → describe and cr…

Anthropic Claude is now a partner node in ComfyUI Drop Claude into any workflow to: → rewrite weak prompts into great ones → describe and critique images intelligently → feed structured text into down

model-releasescomfyui--x

Are Multimodal LLMs Ready for Surveillance? A Reality Check on Zero-Shot Anomaly Detection in the Wild

arXiv:2603.04727v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have demonstrated impressive general competence in video understanding, yet their reliability for rea

safetyarxiv-cs-ai

Asking Back: Interaction-Layer Antidistillation Watermarks

arXiv:2605.16462v1 Announce Type: cross Abstract: Detecting unauthorized knowledge distillation from a deployed LLM API is hard because the defender controls neither the attacker's training pipeline n

ASPI: Seeking Ambiguity Clarification Amplifies Prompt Injection Vulnerability in LLM Agents

arXiv:2605.17324v1 Announce Type: cross Abstract: Clarification-seeking behavior is widely regarded as a desirable property of LLM agents, enabling them to resolve ambiguity before acting on underspec

Bench2Drive-Robust: Benchmarking Closed-Loop Autonomous Driving under Deployment Perturbations

model-releasesarxiv-cs-ro

arXiv:2605.18059v1 Announce Type: new Abstract: Robustness is a critical requirement for deploying autonomous driving systems in the real world. Existing robustness benchmarks for autonomous driving h

Benchmarking inference at scale: coding agents

model-releasestogether-ai-blog

This article presents benchmarking results for AI coding agents evaluated at scale, likely comparing performance metrics such as code generation accuracy, execution success rates, and inference effici

Beyond Superficial Unlearning: Sharpness-Aware Robust Erasure of Hallucinations in Multimodal LLMs

arXiv:2601.16527v2 Announce Type: replace-cross Abstract: Multimodal LLMs are powerful but prone to object hallucinations, which describe non-existent entities and harm reliability. While recent unlea

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks

arXiv:2605.17000v1 Announce Type: cross Abstract: Optimization of LLM training and inference configurations, such as hyperparameters, data mixtures, and prompts, is critical to performance, but it is

Brain-inspired spike-timing plasticity for reliable label-efficient event-camera vision

arXiv:2605.17686v1 Announce Type: new Abstract: Deploying event-camera object detectors is constrained by per-frame labeling requirements and GPU compute demands. This work introduces three local spik

Brain Vascular Age Prediction Using Cerebral Blood Flow Velocity and Machine Learning Algorithms

arXiv:2605.16969v1 Announce Type: new Abstract: Defining vascular age in terms of physiological function has become one focal point of the extensive studies to categorize and track chronological age.

Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codes

arXiv:2605.17755v1 Announce Type: cross Abstract: Clinical coding maps clinical documentation to standardized medical codes, an essential yet time-consuming administrative task that could benefit from

CATA: Continual Machine Unlearning via Conflict-Averse Task Arithmetic

arXiv:2605.18610v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applic

Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents

arXiv:2605.17641v1 Announce Type: new Abstract: Long-horizon LLM agents rely on persistent memory to support interactions across sessions, yet existing memory systems often retrieve context using sema

Causely: A Causal Intelligence Layer for Enterprise AI A Benchmark Study on SRE and Reliability Workflows

arXiv:2605.18327v1 Announce Type: new Abstract: AI agents deployed into SRE workflows currently derive their understanding of environment state from raw observability telemetry at query time, paying a

Code as Agent Harness

arXiv:2605.18747v1 Announce Type: cross Abstract: Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to reposi

safetyarxiv-cs-ai

Constrained Policy Optimization via Sampling-Based Weight-Space Projection

arXiv:2512.13788v2 Announce Type: replace Abstract: Safety-critical learning requires policies that improve performance without leaving the safe operating regime. We study constrained policy learning

Coordinate Heterogeneity Governs Binary Quantization: From InfoNCE to Recall

arXiv:2605.17524v1 Announce Type: new Abstract: Binary quantization (BQ) compresses high-dimensional embeddings into one or two bits per coordinate, enabling nearest neighbor search at extreme speed.

Cost-aware Duration Prediction for Software Upgrades in Datacenters

arXiv:2212.05155v2 Announce Type: replace-cross Abstract: Software upgrades are critical to maintaining server reliability in datacenters. While job duration prediction and scheduling have been extens

CT-DegradBench: A Physics-Informed Benchmark for CT Degradation Detection and Severity Estimation

arXiv:2605.16431v1 Announce Type: new Abstract: Computed tomography (CT) images are frequently degraded by acquisition artifacts, including noise, blur, streaking, aliasing, and metal artifacts. Yet C

CVE-Factory: Scaling Expert-Level Agentic Tasks for Code Security Vulnerability

arXiv:2602.03012v2 Announce Type: replace-cross Abstract: Evaluating and improving the security capabilities of code agents requires high-quality, executable vulnerability tasks. However, existing wor

DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis

arXiv:2601.05527v2 Announce Type: replace-cross Abstract: Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within t

Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning

arXiv:2605.17118v1 Announce Type: new Abstract: Differentiable optimization layers are traditionally integrated in predict-then-optimize frameworks where a neural model estimates parameters that subse

safetyarxiv-cs-lg

Distribution Transformers: Fast Approximate Bayesian Inference With On-The-Fly Prior Adaptation

arXiv:2502.02463v3 Announce Type: replace-cross Abstract: While Bayesian inference provides a principled framework for reasoning under uncertainty, its widespread adoption is limited by the intractabi

DocOS: Towards Proactive Document-Guided Actions in GUI Agents

arXiv:2605.18048v1 Announce Type: new Abstract: While Graphical User Interface (GUI) agents have shown promising performance in automated device interaction, they primarily depend on static parametric

Does Weight Decay Enhance Training Stability?

arXiv:2605.16622v1 Announce Type: new Abstract: In modern deep learning, weight decay is often credited with 'stabilizing' training dynamics, diverging from its classical role as a static regularizati

DriveSafe: A Framework for Risk Detection and Safety Suggestions in Driving Scenarios

arXiv:2605.16892v1 Announce Type: cross Abstract: Comprehensive situational awareness is essential for autonomous vehicles operating in safety-critical environments, as it enables the identification a

EAGT: Echocardiography Augmentation for Generalisability and Transferability

arXiv:2605.16427v1 Announce Type: cross Abstract: Deep learning models for echocardiography segmentation often struggle to generalise across institutions, scanners, and patient populations, where coll

EgoExoMem: Cross-View Memory Reasoning over Synchronized Egocentric and Exocentric Videos

arXiv:2605.18734v1 Announce Type: new Abstract: Egocentric memory is widely used in embodied intelligence, but it may be insufficient for comprehensive spatial-temporal reasoning. Inspired by human re

EmoMind: Decoding Affective Captions from Human Brain fMRI

arXiv:2605.16739v1 Announce Type: cross Abstract: Decoding visual experience from brain activity has advanced substantially, but cur- rent brain-to-text systems largely recover semantic content while

Enhancing Metacognitive AI: Knowledge-Graph Population with Graph-Theoretic LLM Enrichment

arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p

Enhancing Table Reasoning with Deterministic Table-State Rewards

arXiv:2601.22530v2 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for i

Enhancing Train-Free Infinite-Frame Generation for Consistent Long Videos

arXiv:2605.18233v1 Announce Type: new Abstract: Without incurring significant computational overhead, train-free long video generation aims to enable foundation video generation models to produce long

safetyarxiv-cs-cv

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio

Evaluation Drift in LLM Personality Induction: Are We Moving the Goalpost?

arXiv:2605.16996v1 Announce Type: new Abstract: Can large language models reliably express a human-like personality, or are they merely mimicking surface cues without a stable underlying profile? To i

researcharxiv-cs-cl

EveryQuery: Zero-Shot Clinical Prediction via Task-Conditioned Pretraining over Electronic Health Records

arXiv:2603.07900v2 Announce Type: replace Abstract: Foundation models pretrained on electronic health records (EHR) have demonstrated zero-shot clinical prediction capabilities by generating synthetic

EvilGenie: A Reward Hacking Benchmark

arXiv:2511.21654v2 Announce Type: replace Abstract: We introduce EvilGenie, a benchmark for reward hacking in programming settings. We source problems from LiveCodeBench and create an environment in w

Expandable, Compressible, Mineable: Open-World Thermal Image Restoration

arXiv:2605.16967v1 Announce Type: new Abstract: In open-world settings, thermal infrared (TIR) image degradations continuously emerge and evolve, while most existing all-in-one restoration methods are

extit{Don't Guess, Just Ask}: Resolving Ambiguity in Referring Segmentation via Multi-turn Clarification

arXiv:2605.17531v1 Announce Type: new Abstract: Referring segmentation aims to segment the target objects in images or videos based on the textual query. Despite remarkable progress over the past year

extsc{PrivScope}: Task-scoped Disclosure Control for Hybrid Agentic Systems

arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud

Fast Kernel-Space Diffusion for Remote Sensing Pansharpening

arXiv:2505.18991v3 Announce Type: replace Abstract: Pansharpening seeks to fuse high-resolution panchromatic (PAN) and low-resolution multispectral (LRMS) images into a single image with both fine spa