Search: “models”

PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference

arXiv:2604.24971v1 Announce Type: cross Abstract: We present PolyKV, a system in which multiple concurrent inference agents share a single, asymmetrically compressed KV cache pool. Rather than allocat

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PortraVec: Image-Based Portrait Vectorization with Text-Guided Manipulation

DGX agent

arXiv:2410.04182v2 Announce Type: replace Abstract: While portrait sketch generation is a special task in sketch synthesis, most existing methods are pixel-based, limiting their interpretability and e

model-releasesarxiv-cs-cv

29 Apr 2026

ProDrive: Proactive Planning for Autonomous Driving via Ego-Environment Co-Evolution

arXiv:2604.25329v1 Announce Type: new Abstract: End-to-end autonomous driving planners typically generate trajectories from current observations alone. However, real-world driving is highly dynamic, a

safetyarxiv-cs-ro

Progressing beyond Art Masterpieces or Touristic Cliches: how to assess your LLMs for cultural alignment?

arXiv:2604.25654v1 Announce Type: new Abstract: Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- unt

safetyarxiv-cs-cl

PSI-Bench: Towards Clinically Grounded and Interpretable Evaluation of Depression Patient Simulators

arXiv:2604.25840v1 Announce Type: new Abstract: Patient simulators are gaining traction in mental health training by providing scalable exposure to complex and sensitive patient interactions. Simulati

Applications

Robust Deepfake Detection: Mitigating Spatial Attention Drift via Calibrated Complementary Ensembles

arXiv:2604.25889v1 Announce Type: new Abstract: Current deepfake detection models achieve state-of-the-art performance on pristine academic datasets but suffer severe spatial attention drift under rea

applicationsarxiv-cs-cv

Agents

SciDER: Scientific Data-centric End-to-end Researcher

arXiv:2603.01421v2 Announce Type: replace-cross Abstract: Automated scientific discovery with large language models is transforming the research lifecycle from ideation to experimentation, yet existin

agentsarxiv-cs-cl

SecureScan: An AI-Driven Multi-Layer Framework for Malware and Phishing Detection Using Logistic Regression and Threat Intelligence Integration

arXiv:2602.10750v2 Announce Type: replace-cross Abstract: The growing sophistication of modern malware and phishing campaigns has diminished the effectiveness of traditional signature-based intrusion

Self-DACE++: Robust Low-Light Enhancement via Efficient Adaptive Curve Estimation

arXiv:2604.25367v1 Announce Type: new Abstract: In this paper, we present Self-DACE++, an improved unsupervised and lightweight framework for Low-Light Image Enhancement (LLIE), building upon our prev

Subliminal Steering: Stronger Encoding of Hidden Signals

arXiv:2604.25783v1 Announce Type: new Abstract: Subliminal learning describes a student language model inheriting a behavioral bias by fine-tuning on seemingly innocuous data generated by a biased tea

safetyarxiv-cs-cl

TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning

arXiv:2604.25898v1 Announce Type: new Abstract: Continual offline reinforcement learning (CORL) aims to learn a sequence of tasks from datasets collected over time while preserving performance on prev

Variational Neural Belief Parameterizations for Robust Dexterous Grasping under Multimodal Uncertainty

arXiv:2604.25897v1 Announce Type: cross Abstract: Contact variability, sensing uncertainty, and external disturbances make grasp execution stochastic. Expected-quality objectives ignore tail outcomes

Why Search When You Can Transfer? Amortized Agentic Workflow Design from Structural Priors

arXiv:2604.25012v1 Announce Type: new Abstract: Automated agentic workflow design currently relies on per-task iterative search, which is computationally prohibitive and fails to reuse structural know

6thGrid-Net: Unified Remote Sensing Image Dehazing Based on Color Restoration and Edge-Preserving

arXiv:2604.24149v1 Announce Type: new Abstract: Remote sensing images are frequently degraded by adverse weather conditions, particularly clouds and haze, which severely impair downstream applications

A General Framework for Generative Self-supervised Learning in Non-invasive Estimation of Physiological Parameters Using Photoplethysmography

arXiv:2604.22780v1 Announce Type: cross Abstract: Aligning physiological parameter labels with large-scale photoplethysmographic (PPG) data for deep learning is challenging and resource-intensive. Whi

AD-Relight: Training-Free Banner Relighting via Illumination Translation with Diffusion Priors

arXiv:2604.24407v1 Announce Type: new Abstract: The recent surge in content consumption through streaming services has driven a growing demand for personalized content. Personalized advertisements (ad

researcharxiv-cs-cv

Adaptive-Distribution Randomized Neural Networks for PDEs: A Low-Dimensional Distribution-Learning Framework

arXiv:2604.23999v1 Announce Type: cross Abstract: Randomized neural networks (RaNNs) are attractive for partial differential equations (PDEs) because they replace expensive end-to-end training with a

AgentHER: Hindsight Experience Replay for LLM Agent Trajectory Relabeling

arXiv:2603.21357v3 Announce Type: replace Abstract: LLM agents fail on the majority of real-world tasks -- GPT-4o succeeds on fewer than 15% of WebArena navigation tasks and below 55% pass@1 on ToolBe

Agentic Hives: Equilibrium, Indeterminacy, and Endogenous Cycles in Self-Organizing Multi-Agent Systems

arXiv:2603.00130v2 Announce Type: replace-cross Abstract: Current multi-agent AI systems operate with a fixed number of agents whose roles are specified at design time. No formal theory governs when a

Agentic Witnessing: Pragmatic and Scalable TEE-Enabled Privacy-Preserving Auditing

arXiv:2604.24203v1 Announce Type: cross Abstract: Auditing the semantic properties of proprietary data creates a fundamental tension: verification requires transparent access, while proprietary rights

Aligned Multi-View Scripts for Universal Chart-to-Code Generation

arXiv:2604.24559v1 Announce Type: cross Abstract: Chart-to-code generation converts a chart image into an executable plotting script, enabling faithful reproduction and editable visualizations. Existi

An Intelligent Fault Diagnosis Method for General Aviation Aircraft Based on Multi-Fidelity Digital Twin and FMEA Knowledge Enhancement

arXiv:2604.22777v1 Announce Type: new Abstract: Fault diagnosis of general aviation aircraft faces challenges including scarce real fault data, diverse fault types, and weak fault signatures. This pap

researcharxiv-cs-ai

AnalogRetriever: Learning Cross-Modal Representations for Analog Circuit Retrieval

arXiv:2604.23195v1 Announce Type: cross Abstract: Analog circuit design relies heavily on reusing existing intellectual property (IP), yet searching across heterogeneous representations such as SPICE

Agents

Anonymization-Enhanced Privacy Protection for Mobile GUI Agents: Available but Invisible

arXiv:2602.10139v3 Announce Type: replace-cross Abstract: Mobile Graphical User Interface (GUI) agents have demonstrated strong capabilities in automating complex smartphone tasks by leveraging multim

agentsarxiv-cs-ai

Applied AI-Enhanced RF Interference Rejection

arXiv:2604.22816v1 Announce Type: cross Abstract: AI-enhanced interference rejection in radio frequency (RF) transmissions has recently attracted interest because deep learning approaches trained on b

researcharxiv-cs-ai

ArgRE: Formal Argumentation for Conflict Resolution in Multi-Agent Requirements Negotiation

arXiv:2604.23124v1 Announce Type: cross Abstract: As software systems grow in complexity, they must satisfy an increasing number of competing quality attributes, making it essential to balance them in

safetyarxiv-cs-ai

Artificial General Intelligence Forecasting and Scenario Analysis: State of the Field, Methodological Gaps, and Strategic Implications

arXiv:2604.22766v1 Announce Type: cross Abstract: In this report, we review the current state of methodologies to forecast the arrival of artificial general intelligence, assess their reliability, and

AutoCompress: Critical Layer Isolation for Efficient Transformer Compression

arXiv:2604.22786v1 Announce Type: new Abstract: We present AutoCompress, a transformer compression method motivated by an empirical finding: in small transformers, Layer 0 carries disproportionately h

Avionic Main Fuel Pump Simulation and Fault-Diagnosis Benchmark

arXiv:2604.22869v1 Announce Type: cross Abstract: In many cyber-physical systems, especially in critical applications such as aeroplanes, data to train anomaly detection and diagnosis algorithms is la

BERT-APC: A Reference-free Framework for Automatic Pitch Correction via Musical Context Inference

arXiv:2511.20006v2 Announce Type: replace-cross Abstract: Automatic Pitch Correction (APC) enhances vocal recordings by aligning pitch deviations with intended musical notes. However, existing APC sys

researcharxiv-cs-ai

Beyond the Attention Stability Boundary: Agentic Self-Synthesizing Reasoning Protocols

arXiv:2604.24512v1 Announce Type: new Abstract: As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as

Breaking Lock-In: Preserving Steerability under Low-Data VLA Post-Training

arXiv:2604.23121v1 Announce Type: cross Abstract: Have you ever post-trained a generalist vision-language-action (VLA) policy on a small demonstration dataset, only to find that it stops responding to

safetyarxiv-cs-cv

BRIEF-Pro: Universal Context Compression with Short-to-Long Synthesis for Fast and Accurate Multi-Hop Reasoning

arXiv:2510.13799v2 Announce Type: replace Abstract: As retrieval-augmented generation (RAG) tackles complex tasks, increasingly expanded contexts offer richer information, but at the cost of higher la

researcharxiv-cs-cl

Causal Representation Learning from General Environments under Nonparametric Mixing

arXiv:2604.23800v1 Announce Type: new Abstract: Causal representation learning aims to recover the latent causal variables and their causal relations, typically represented by directed acyclic graphs

researcharxiv-cs-lg

Applications

Chat-Scene++: Exploiting Context-Rich Object Identification for 3D LLM

arXiv:2603.27507v2 Announce Type: replace Abstract: Recent advancements in multi-modal large language models (MLLMs) have shown strong potential for 3D scene understanding. However, existing methods s

applicationsarxiv-cs-cv

Agents

ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents

arXiv:2604.23069v1 Announce Type: new Abstract: Large language model (LLM) agents often struggle in long-context interactions. As the agent accumulates more interaction history, context management app

agentsarxiv-cs-cl

DARC-CLIP: Dynamic Adaptive Refinement with Cross-Attention for Meme Understanding

arXiv:2604.23214v1 Announce Type: new Abstract: Memes convey meaning through the interaction of visual and textual signals, often combining humor, irony, and offense in subtle ways. Detecting harmful

DeepTaxon: An Interpretable Retrieval-Augmented Multimodal Framework for Unified Species Identification and Discovery

arXiv:2604.24029v1 Announce Type: cross Abstract: Identifying species in biology among tens of thousands of visually similar taxa while discovering unknown species in open-world environments remains a

Applications

Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring

arXiv:2511.23036v2 Announce Type: replace-cross Abstract: Explaining online time series monitoring models is crucial across sensitive domains such as healthcare and finance, where temporal and context

applicationsarxiv-cs-ai

Dialysis Risk Prediction and Treatment Effect Estimation for AKI patients using Longitudinal Electronic Health Records

arXiv:2604.24547v1 Announce Type: new Abstract: Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures infl

researcharxiv-cs-lg

Discovering Agentic Safety Specifications from 1-Bit Danger Signals

arXiv:2604.23210v1 Announce Type: new Abstract: Can large language model agents discover hidden safety objectives through experience alone? We introduce EPO-Safe (Experiential Prompt Optimization for

safetyarxiv-cs-ai

Distilling Self-Consistency into Verbal Confidence: A Pre-Registered Negative Result and Post-Hoc Rescue on Gemma 3 4B

arXiv:2604.24070v1 Announce Type: cross Abstract: Small instruct-tuned LLMs produce degenerate verbal confidence under minimal elicitation: ceiling rates above 95%, near-chance Type-2 AUROC, and Inval

Do Synthetic Trajectories Reflect Real Reward Hacking? A Systematic Study on Monitoring In-the-Wild Hacking in Code Generation

arXiv:2604.23488v1 Announce Type: new Abstract: Reward hacking in code generation, where models exploit evaluation loopholes to obtain full reward without correctly solving the tasks, poses a critical

safetyarxiv-cs-lg

DyABD: The Abdominal Muscle Segmentation in Dynamic MRI Benchmark

arXiv:2604.23187v1 Announce Type: cross Abstract: This work introduces DyABD, a novel and complex benchmark dataset of dynamic abdominal MRIs from patients with abdominal hernias and associated high q

DynProto: Dynamic Prototype Evolution for Out-of-Distribution Detection

arXiv:2604.23729v1 Announce Type: new Abstract: Recent studies show that using potential out-of-distribution (OOD) labels from large corpora as auxiliary information can improve OOD detection in visio

Efficient learning by implicit exploration in bandit problems with side observations

arXiv:2604.24555v1 Announce Type: new Abstract: We consider online learning problems under a partial observability model capturing situations where the information conveyed to the learner is between f

researcharxiv-cs-lg

EMCompress: Video-LLMs with Endomorphic Multimodal Compression

arXiv:2508.21094v3 Announce Type: replace Abstract: Video-LLMs face a fundamental tension in long-video reasoning: static, sparse frame sampling either dilutes evidence across task-irrelevant segments

Empirical Ablation and Ensemble Optimization of a Convolutional Neural Network for CIFAR-10 Classification

arXiv:2604.23861v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) remain a central approach in image classification, but their performance depends strongly on architectural and tr