Search: “models”

Declarative Data Services: Structured Agentic Discovery for Composing Data Systems

arXiv:2605.20690v1 Announce Type: new Abstract: Agentic discovery has shown that LLM-driven search can find novel algorithms, designs, and code under benchmark conditions. Translating the paradigm to

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Research

Detecting Trojaned DNNs via Spectral Regression Analysis

DGX agent

arXiv:2605.21146v1 Announce Type: cross Abstract: Modern DNNs are repeatedly fine-tuned to incorporate new data and functionality. This evolutionary workflow introduces a security risk when updated da

researcharxiv-cs-ai

22 May 2026

Direct content-based retrieval from music scores images

arXiv:2605.22255v1 Announce Type: new Abstract: The digitization of musical scores plays a crucial role in their preservation and accessibility, yet information retrieval still depends mainly on metad

Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detection

arXiv:2605.21964v1 Announce Type: new Abstract: Computational imaging enables compact infrared systems, but deep-learning pipelines that combine image reconstruction and object detection often introdu

Evaluating Temporal Semantic Caching and Workflow Optimization in Agentic Plan-Execute Pipelines

arXiv:2605.20630v1 Announce Type: new Abstract: Industrial asset operations workflows are latency-sensitive because a single user query may require coordination over sensor data, work orders, failure

Event-Illumination Collaborative Low-light Image Enhancement with a High-resolution Real-world Dataset

arXiv:2605.22186v1 Announce Type: new Abstract: Event-based low-light image enhancement (LIE) methods mainly focus on incorporating high dynamic range (HDR) information from events while overlooking t

Faithful-MR1: Faithful Multimodal Reasoning via Anchoring and Reinforcing Visual Attention

arXiv:2605.22072v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising paradigm for advancing complex reasoning in large language models, and

researcharxiv-cs-cl

FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments

arXiv:2605.22018v1 Announce Type: new Abstract: The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collectio

GenEvolve: Self-Evolving Image Generation Agents via Tool-Orchestrated Visual Experience Distillation

arXiv:2605.21605v1 Announce Type: new Abstract: Open-ended image generation is no longer a simple prompt-to-image problem. High-quality generation often requires an agent to combine a model's internal

safetyarxiv-cs-cv

GrandGuard: Taxonomy, Benchmark, and Safeguards for Elderly-Chatbot Interaction Safety

arXiv:2605.20203v1 Announce Type: cross Abstract: As older adults increasingly use LLM-based chatbots for companionship and assistance, a safety gap is emerging. Older adults may face vulnerabilities

Guided Trajectory Optimization with Sparse Scaling for Test-Time Diffusion

arXiv:2605.21907v1 Announce Type: new Abstract: The efficient Test-Time Scaling (TTS) paradigm offers a promising perspective for enhancing the generation performance of diffusion models. However, cur

Harder to Defend: Towards Chinese Toxicity Attacks via Implicit Enhancement and Obfuscation Rewriting

arXiv:2605.22258v1 Announce Type: new Abstract: Large language models (LLMs) require robust toxicity evaluation beyond explicit wording. This setting remains underexplored in Chinese, where toxicity m

Hierarchical Variational Policies for Reward-Guided Diffusion

arXiv:2605.21661v1 Announce Type: cross Abstract: Adapting pretrained diffusion models to downstream objectives such as inverse problems often requires expensive test-time guidance or optimization. We

safetyarxiv-cs-cv

Agents

ImProver: Agent-Based Automated Proof Optimization

arXiv:2410.04753v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been used to generate formal proofs of mathematical theorems in proofs assistants such as Lean. However, we

agentsarxiv-cs-cl

LANG: Reinforcement Learning for Multilingual Reasoning with Language-Adaptive Hint Guidance

arXiv:2605.22567v1 Announce Type: new Abstract: Reinforcement learning has proven effective for enhancing multi-step reasoning in large language models (LLMs), yet its benefits have not fully translat

LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning

arXiv:2605.22012v1 Announce Type: new Abstract: Joint audio-visual reasoning is essential for omnimodal understanding, yet current multimodal large language models (MLLMs) still struggle when reasonin

researcharxiv-cs-cl

MaSC: A Masked Similarity Metric for Evaluating Concept-Driven Generation

arXiv:2605.22469v1 Announce Type: new Abstract: Evaluating single-concept personalization in text-to-image diffusion requires measuring both concept preservation, which captures identity fidelity to a

Matching with Deliberation: Test-Time Evolutionary Hierarchical Multi-Agents for Zero-Shot Compositional Image Retrieval

arXiv:2605.22478v1 Announce Type: new Abstract: Zero-Shot Compositional Image Retrieval (ZS-CIR) requires both preserving the visual continuity of the reference image and faithfully executing the sema

Applications

MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics via Learning Residual Anisotropy

arXiv:2605.22597v1 Announce Type: cross Abstract: Learning real-world dynamics from visual observations is crucial for various domains. A common strategy is to calibrate simulators by estimating physi

applicationsarxiv-cs-ro

One Sentence, One Drama: Personalized Short-Form Drama Generation via Multi-Agent Systems

arXiv:2605.22144v1 Announce Type: new Abstract: Existing approaches for digital short-drama production typically rely on one-shot LLM generated scripts and loosely coupled pipelines, which fail to sat

Open-World Evaluations for Measuring Frontier AI Capabilities

arXiv:2605.20520v1 Announce Type: new Abstract: Benchmark-based evaluation remains important for tracking frontier AI progress. But it can both overstate and understate deployed capability because it

Optimus: A Robust Defense Framework for Mitigating Toxicity while Fine-Tuning Conversational AI

arXiv:2507.05660v3 Announce Type: replace-cross Abstract: Customizing Large Language Models (LLMs) on untrusted datasets poses severe risks of injecting toxic behaviors. In this work, we introduce Opt

PartCo: Part-Level Correspondence Priors Enhance Category Discovery

arXiv:2509.22769v2 Announce Type: replace Abstract: Generalized Category Discovery (GCD) aims to identify both known and novel categories within unlabeled data by leveraging a set of labeled examples

Physiology and Anatomy Aware Inverse Inference of Myocardial Infarction for Cardiac Digital Twin

arXiv:2605.22044v1 Announce Type: new Abstract: Accurate localization of myocardial infarction is essential for risk stratification. While LGE-MRI remains the gold standard, it is resource-intensive.

ProcBench: Evaluating Process-Level Defects and Control Preservation in LLM Coding Agents

arXiv:2605.20251v2 Announce Type: cross Abstract: Existing benchmarks for LLM coding agents primarily evaluate final outcomes. While useful for measuring overall capability, these metrics provide limi

Ratchet: A Minimal Hygiene Recipe for Self-Evolving LLM Agents

model-releasesarxiv-cs-cl

arXiv:2605.22148v1 Announce Type: cross Abstract: Self-evolving skill libraries, pioneered by Voyager, let frozen LLM agents accumulate reusable knowledge without weight updates, yet recent evaluation

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning

arXiv:2605.22511v1 Announce Type: cross Abstract: Post-training has become the dominant recipe for turning a language model into a competent search-augmented reasoning agent. A line of recent work pus

Seeing the Poem: Image-Semantic Detection of AI-Generated Modern Chinese Poetry with MLLMs

model-releasesarxiv-cs-cl

arXiv:2605.22654v1 Announce Type: new Abstract: Previous detection studies have shown that LLMs cannot be effectively used as detectors, but these studies have not addressed modern Chinese poetry. Mor

Tutorials

Segment Anything with Motion, Geometry, and Semantic Adaptation for Complex Nonlinear Visual Object Tracking

arXiv:2605.22538v1 Announce Type: new Abstract: Traditional visual object tracking (VOT) methods typically rely on task-specific supervised training, limiting their generalization to unseen objects an

tutorialsarxiv-cs-cv

Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews

arXiv:2605.21713v1 Announce Type: new Abstract: How can we distinguish whether a peer review was written by a human or generated by an AI model? We argue that, in this setting, authorship should not b

researcharxiv-cs-cl

Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment

arXiv:2605.22677v1 Announce Type: new Abstract: Deploying vision models across devices with varying resource constraints, or even on a single device where available compute fluctuates due to battery s

Applications

Spectral Tail Auxiliary Learning for AI-Generated Image Detection

arXiv:2605.22751v1 Announce Type: new Abstract: As generative image models evolve rapidly, the perceptual gap between generated and real images continues to narrow, making AI-generated image detection

applicationsarxiv-cs-cv

Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling

arXiv:2605.22484v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at tasks like zero-shot classification and cross-modal retrieval by mapping images and text to a shared space, but t

safetyarxiv-cs-cv

Targeting Clause Type Distributions: a Picklock for Random Satisfiability Problems

arXiv:2605.20328v1 Announce Type: cross Abstract: Optimization problems such as the NP-complete 3-SAT provide an important benchmark for the difficult task of finding ground-states in strongly correla

Teaching AI Through Benchmark Construction: QuestBench as a Course-Based Practice for Accountable Knowledge Work

arXiv:2605.21413v2 Announce Type: new Abstract: As AI becomes part of everyday learning, many courses teach students to use it mainly as a productivity tool: how to prompt, search, summarize, write, c

Translating Signals to Languages for sEMG-Based Activity Recognition

arXiv:2605.22403v1 Announce Type: new Abstract: Surface electromyography (sEMG) signal-based activity recognition has attracted increasing research attention in recent years. To develop accurate sEMG

Tutorials

Unified Data Selection for LLM Reasoning

arXiv:2605.22389v1 Announce Type: new Abstract: Effectively training Large Language Models (LLMs) for complex, long-CoT reasoning is often bottlenecked by the need for massive high-quality reasoning d

tutorialsarxiv-cs-cl

VEELA: A Clinically-Constrained Benchmark for Liver Vessel Segmentation in Computed Tomography Angiography

arXiv:2605.22357v1 Announce Type: new Abstract: Accurate segmentation of hepatic and portal vessels in contrast-enhanced computed tomography angiography (CTA) remains challenging due to complex vascul

Zero-Shot Temporal Action Localization Through Textual Guidance

arXiv:2605.22201v1 Announce Type: new Abstract: Zero-shot temporal action localization (ZS-TAL) consists of classifying and localizing actions in untrimmed videos, where action classes are unseen at t

A Deployment Audit of Release-Side Risk in Conformal Triage under Prevalence Shift

arXiv:2605.20956v1 Announce Type: new Abstract: Conformal triage converts predictive scores into deployment actions that either release a case, flag it for urgent attention, or defer it to human revie

A strongly annotated passive acoustic dataset for tropical bird monitoring

arXiv:2605.20578v1 Announce Type: cross Abstract: Passive acoustic monitoring enables continuous, non-invasive biodiversity assessment across diverse ecosystems. The scale of these datasets has driven

A Unified Framework for Uncertainty-Aware Explainable Artificial Intelligence: A Case Study in Power Quality Disturbance Classification

arXiv:2605.21114v1 Announce Type: new Abstract: Post-hoc explainable AI (XAI) methods typically produce deterministic attribution maps, whereas Bayesian neural networks (BNNs) induce a distribution ov

Tutorials

Adaptive Probe-based Steering for Robust LLM Jailbreaking

arXiv:2605.20286v1 Announce Type: cross Abstract: Recent work has demonstrated the potential of contrastive steering for jailbreaking Large Language Models (LLMs). However, existing methods rely on li

tutorialsarxiv-cs-lg

Advantage Collapse in Group Relative Policy Optimization: Diagnosis and Mitigation

arXiv:2605.21125v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO), a prominent algorithm within the Reinforcement Learning from Verifiable Rewards (RLVR) framework, has achieve

safetyarxiv-cs-lg

Adversarial Robustness in One-Stage Learning-to-Defer

arXiv:2510.10988v2 Announce Type: replace-cross Abstract: Learning-to-Defer (L2D) enables hybrid decision-making by routing inputs either to a predictor or to external experts. While promising, L2D is

AFD-INSTRUCTION: A Comprehensive Antibody Instruction Dataset with Functional Annotations for LLM-Based Understanding and Design

arXiv:2602.04916v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have significantly advanced protein representation learning. However, their capacity to interpret and design anti

AGPO: Adaptive Group Policy Optimization with Dual Statistical Feedback

arXiv:2605.20722v1 Announce Type: new Abstract: Reinforcement learning improves LLM reasoning, but PPO/GRPO typically use fixed clipping and decoding temperature, which makes training brittle and tuni

AI-Assisted Scientific Assessment: A Case Study on Climate Change

model-releasesarxiv-cs-cl

arXiv:2602.09723v2 Announce Type: replace Abstract: The emerging paradigm of AI co-scientists focuses on tasks characterized by repeatable verification, where agents explore search spaces in 'guess an