Search: “models”

A Large-Scale Comparative Analysis of Imputation Methods for Single-Cell RNA Sequencing Data

model-releasesarxiv-cs-lg

arXiv:2603.24626v2 Announce Type: replace-cross Abstract: Background: Single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at cellular resolution but is inherently affected by spar

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AAPO: Enhancing the Reasoning Capabilities of LLMs with Advantage Margin

DGX agent

arXiv:2505.14264v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has emerged as an effective approach for enhancing the reasoning capabilities of large language models (LLMs), esp

safetyarxiv-cs-cl

15 Apr 2026

Active Imitation Learning for Thermal- and Kernel-Aware LFM Inference on 3D S-NUCA Many-Cores

arXiv:2604.11948v1 Announce Type: new Abstract: Large Foundation Model (LFM) inference is both memory- and compute-intensive, traditionally relying on GPUs. However, the limited availability and high

safetyarxiv-cs-lg

Agents

Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

arXiv:2604.12129v1 Announce Type: new Abstract: The transition from stateless model inference to stateful agentic execution is reshaping the systems assumptions underlying modern AI infrastructure. Wh

agentsarxiv-cs-ai

AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text Generation

arXiv:2604.06812v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucinati

researcharxiv-cs-cl

AlphaEval: Evaluating Agents in Production

model-releasesarxiv-cs-cl

arXiv:2604.12162v1 Announce Type: new Abstract: The rapid deployment of AI agents in commercial settings has outpaced the development of evaluation methodologies that reflect production realities. Exi

ASTRA: Let Arbitrary Subjects Transform in Video Editing

model-releasesarxiv-cs-cv

arXiv:2510.01186v2 Announce Type: replace Abstract: While existing video editing methods excel with single subjects, they struggle in dense, multi-subject scenes, frequently suffering from attention d

Agents

Beyond Majority Voting: Efficient Best-Of-N with Radial Consensus Score

arXiv:2604.12196v1 Announce Type: new Abstract: Large language models (LLMs) frequently generate multiple candidate responses for a given prompt, yet selecting the most reliable one remains challengin

agentsarxiv-cs-cl

BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning

arXiv:2604.12686v1 Announce Type: cross Abstract: Recent advances in deep learning underscore the need for systems that can not only acquire new knowledge through Continual Learning (CL) but also remo

CODESTRUCT: Code Agents over Structured Action Spaces

arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin

Combating Pattern and Content Bias: Adversarial Feature Learning for Generalized AI-Generated Image Detection

arXiv:2604.12353v1 Announce Type: new Abstract: In recent years, the rapid development of generative artificial intelligence technology has significantly lowered the barrier to creating high-quality f

safetyarxiv-cs-cv

Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors

arXiv:2604.12359v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines, yet this deployment also enlarges the supply-chain atta

safetyarxiv-cs-cl

CropVLM: Learning to Zoom for Fine-Grained Vision-Language Perception

arXiv:2511.19820v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) often struggle with tasks that require fine-grained image understanding, such as scene-text recognition or docum

researcharxiv-cs-ai

Cross-Attentive Multiview Fusion of Vision-Language Embeddings

arXiv:2604.12551v1 Announce Type: new Abstract: Vision-language models have been key to the development of open-vocabulary 2D semantic segmentation. Lifting these models from 2D images to 3D scenes, h

Cross-Cultural Simulation of Citizen Emotional Responses to Bureaucratic Red Tape Using LLM Agents

arXiv:2604.12545v1 Announce Type: new Abstract: Improving policymaking is a central concern in public administration. Prior human subject studies reveal substantial cross-cultural differences in citiz

DocSeeker: Structured Visual Reasoning with Evidence Grounding for Long Document Understanding

arXiv:2604.12812v1 Announce Type: new Abstract: Existing Multimodal Large Language Models (MLLMs) suffer from significant performance degradation on the long document understanding task as document le

Every Picture Tells a Dangerous Story: Memory-Augmented Multi-Agent Jailbreak Attacks on VLMs

arXiv:2604.12616v1 Announce Type: new Abstract: The rapid evolution of Vision-Language Models (VLMs) has catalyzed unprecedented capabilities in artificial intelligence; however, this continuous modal

FeaXDrive: Feasibility-aware Trajectory-Centric Diffusion Planning for End-to-End Autonomous Driving

model-releasesarxiv-cs-lg

arXiv:2604.12656v1 Announce Type: cross Abstract: End-to-end diffusion planning has shown strong potential for autonomous driving, but the physical feasibility of generated trajectories remains insuff

Fragile Reconstruction: Adversarial Vulnerability of Reconstruction-Based Detectors for Diffusion-Generated Images

arXiv:2604.12781v1 Announce Type: new Abstract: Recently, detecting AI-generated images produced by diffusion-based models has attracted increasing attention due to their potential threat to safety. A

safetyarxiv-cs-cv

From Attenuation to Attention: Variational Information Flow Manipulation for Fine-Grained Visual Perception

arXiv:2604.12508v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in general visual understanding, they frequently falter in fine

Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering Tasks with Generative Optimization

arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl

Applications

GRADE: Probing Knowledge Gaps in LLMs through Gradient Subspace Dynamics

arXiv:2604.02830v2 Announce Type: replace Abstract: Detecting whether a model's internal knowledge is sufficient to correctly answer a given question is a fundamental challenge in deploying responsibl

applicationsarxiv-cs-cl

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation

arXiv:2603.07926v3 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. H

Incentivizing High-Quality Human Annotations with Golden Questions

arXiv:2505.19134v2 Announce Type: replace-cross Abstract: Human-annotated data plays a vital role in training large language models (LLMs), such as supervised fine-tuning and human preference alignmen

safetyarxiv-cs-lg

Applications

Influence Strength Estimation in Hyperbolic Space for Social Influence Maximization

arXiv:2502.13571v2 Announce Type: replace-cross Abstract: The Influence Maximization (IM) problem aims to find a small set of influential users to maximize their influence spread in a social network.

applicationsarxiv-cs-lg

LLMs Struggle with Abstract Meaning Comprehension More Than Expected

arXiv:2604.12018v1 Announce Type: cross Abstract: Understanding abstract meanings is crucial for advanced language comprehension. Despite extensive research, abstract words remain challenging due to t

researcharxiv-cs-ai

MISID: A Multimodal Multi-turn Dataset for Complex Intent Recognition in Strategic Deception Games

arXiv:2604.12700v1 Announce Type: new Abstract: Understanding human intent in complex multi-turn interactions remains a fundamental challenge in human-computer interaction and behavioral analysis. Whi

Narrative-Driven Paper-to-Slide Generation via ArcDeck

arXiv:2604.11969v1 Announce Type: new Abstract: We introduce ArcDeck, a multi-agent framework that formulates paper-to-slide generation as a structured narrative reconstruction task. Unlike existing m

On the continuum limit of t-SNE for data visualization

model-releasesarxiv-cs-lg

arXiv:2604.12041v1 Announce Type: cross Abstract: This work is concerned with the continuum limit of a graph-based data visualization technique called the t-Distributed Stochastic Neighbor Embedding (

Policy-Invisible Violations in LLM-Based Agents

arXiv:2604.12177v1 Announce Type: new Abstract: LLM-based agents can execute actions that are syntactically valid, user-sanctioned, and semantically appropriate, yet still violate organizational polic

Refined Differentially Private Linear Regression via Extension of a Free Lunch Result

arXiv:2604.11820v1 Announce Type: cross Abstract: As data-privacy regulations tighten and statistical models are increasingly deployed on sensitive human-sourced data, privacy-preserving linear regres

researcharxiv-cs-lg

RPG-SAM: Reliability-Weighted Prototypes and Geometric Adaptive Threshold Selection for Training-Free One-Shot Polyp Segmentation

model-releasesarxiv-cs-cv

arXiv:2603.07436v2 Announce Type: replace Abstract: Training-free one-shot segmentation offers a scalable alternative to expert annotations where knowledge is often transferred from support images and

Socrates Loss: Unifying Confidence Calibration and Classification by Leveraging the Unknown

arXiv:2604.12245v1 Announce Type: cross Abstract: Deep neural networks, despite their high accuracy, often exhibit poor confidence calibration, limiting their reliability in high-stakes applications.

StoryScope: Investigating idiosyncrasies in AI fiction

model-releasesarxiv-cs-cl

arXiv:2604.03136v4 Announce Type: replace Abstract: As AI-generated fiction becomes increasingly prevalent, questions of authorship and originality are becoming central to how written work is evaluate

Subspace-Guided Feature Reconstruction for Unsupervised Anomaly Localization

model-releasesarxiv-cs-cv

arXiv:2309.13904v3 Announce Type: replace Abstract: Unsupervised anomaly localization aims to identify anomalous regions that deviate from normal sample patterns. Most recent methods perform feature m

TEMPLATEFUZZ: Fine-Grained Chat Template Fuzzing for Jailbreaking and Red Teaming LLMs

arXiv:2604.12232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed across diverse domains, yet their vulnerability to jailbreak attacks, where adversarial inputs

Agents

Thermodynamic Liquid Manifold Networks: Physics-Bounded Deep Learning for Solar Forecasting in Autonomous Off-Grid Microgrids

arXiv:2604.11909v1 Announce Type: cross Abstract: The stable operation of autonomous off-grid photovoltaic systems requires solar forecasting algorithms that respect atmospheric thermodynamics. Contem

agentsarxiv-cs-ai

Token-Level Policy Optimization: Linking Group-Level Rewards to Token-Level Aggregation via Sequence-Level Likelihood

arXiv:2604.12736v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has significantly advanced the reasoning ability of large language models (LLMs), particularly in their mathem

safetyarxiv-cs-cl

Towards Long-horizon Agentic Multimodal Search

arXiv:2604.12890v1 Announce Type: cross Abstract: Multimodal deep search agents have shown great potential in solving complex tasks by iteratively collecting textual and visual evidence. However, mana

Towards Realistic and Consistent Orbital Video Generation via 3D Foundation Priors

arXiv:2604.12309v1 Announce Type: new Abstract: We present a novel method for generating geometrically realistic and consistent orbital videos from a single image of an object. Existing video generati

Tree Learning: A Multi-Skill Continual Learning Framework for Humanoid Robots

model-releasesarxiv-cs-ro

arXiv:2604.12909v1 Announce Type: new Abstract: As reinforcement learning for humanoid robots evolves from single-task to multi-skill paradigms, efficiently expanding new skills while avoiding catastr

Visual Preference Optimization with Rubric Rewards

arXiv:2604.13029v1 Announce Type: cross Abstract: The effectiveness of Direct Preference Optimization (DPO) depends on preference data that reflect the quality differences that matter in multimodal ta

Local Ai

VPTracker: Global Vision-Language Tracking via Visual Prompt

arXiv:2512.22799v2 Announce Type: replace Abstract: Vision-Language Tracking aims to continuously localize objects described by a visual template and a language description. Existing methods, however,

local-aiarxiv-cs-cv

X-VC: Zero-shot Streaming Voice Conversion in Codec Space

arXiv:2604.12456v1 Announce Type: cross Abstract: Zero-shot voice conversion (VC) aims to convert a source utterance into the voice of an unseen target speaker while preserving its linguistic content.

ACE-Bench: A Lightweight Benchmark for Evaluating Azure SDK Usage Correctness

arXiv:2604.09564v1 Announce Type: cross Abstract: We present ACE-Bench (Azure SDK Coding Evaluation Benchmark), an execution-free benchmark that provides fast, reproducible pass or fail signals for wh

Adversarial Video Promotion Against Text-to-Video Retrieval

arXiv:2508.06964v3 Announce Type: replace Abstract: Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined.

Agent^2 RL-Bench: Can LLM Agents Engineer Agentic RL Post-Training?

arXiv:2604.10547v1 Announce Type: new Abstract: We introduce Agent^2 RL-Bench, a benchmark for evaluating agentic RL post-training -- whether LLM agents can autonomously design, implement, and run com

Are Pretrained Image Matchers Good Enough for SAR-Optical Satellite Registration?

arXiv:2604.10217v1 Announce Type: new Abstract: Cross-modal optical-SAR (Synthetic Aperture Radar) registration is a bottleneck for disaster-response via remote sensing, yet modern image matchers are