Search: “framework”

Act Wisely: Cultivating Meta-Cognitive Tool Use in Agentic Multimodal Models

arXiv:2604.08545v1 Announce Type: new Abstract: The advent of agentic multimodal models has empowered systems to actively interact with external environments. However, current agents suffer from a pro

agentsarxiv-cs-cv

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Action Without Interaction: Probing the Physical Foundations of Video LMMs via Contact-Release Detection

DGX agent

arXiv:2511.20162v2 Announce Type: replace Abstract: Large multi-modal models (LMMs) show increasing performance in realistic visual tasks for images and, more recently, for videos. For example, given

model-releasesarxiv-cs-cv

10 Apr 2026

Adapting Foundation Models for Annotation-Efficient Adnexal Mass Segmentation in Cine Images

arXiv:2604.08045v1 Announce Type: new Abstract: Adnexal mass evaluation via ultrasound is a challenging clinical task, often hindered by subjective interpretation and significant inter-observer variab

researcharxiv-cs-cv

Applications

Adaptive Differential Privacy for Federated Medical Image Segmentation Across Diverse Modalities

arXiv:2604.06518v1 Announce Type: cross Abstract: Large volumes of medical data remain underutilized because centralizing distributed data is often infeasible due to strict privacy regulations and ins

applicationsarxiv-cs-ai

Adaptive Symmetrization of the KL Divergence

arXiv:2511.11159v2 Announce Type: replace Abstract: Many tasks in machine learning can be described as or reduced to learning a probability distribution given a finite set of samples. A common approac

Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest

arXiv:2604.08525v1 Announce Type: cross Abstract: Today's large language models (LLMs) are trained to align with user preferences through methods such as reinforcement learning. Yet models are beginni

Agree! Such sub agents are going to be big

The specific tweet (status ID 2042726390617764234) could not be retrieved directly, as it does not appear in available search results and X/Twitter requires authentication to access individual post...

agentsharrison-chase--x

AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization

model-releasesarxiv-cs-lg

arXiv:2503.03088v4 Announce Type: replace-cross Abstract: The Segment Anything Model (SAM) has revolutionized image and video segmentation with its powerful zero-shot capabilities. However, its massiv

AI-Driven Research for Databases

arXiv:2604.06566v1 Announce Type: cross Abstract: As the complexity of modern workloads and hardware increasingly outpaces human research and engineering capacity, existing methods for database perfor

safetyarxiv-cs-ai

Algebraic Diversity: Group-Theoretic Spectral Estimation from Single Observations

arXiv:2604.03634v2 Announce Type: replace Abstract: We establish that temporal averaging over multiple observations is the degenerate case of algebraic group action with the trivial group G={e}. A

Alloc-MoE: Budget-Aware Expert Activation Allocation for Efficient Mixture-of-Experts Inference

arXiv:2604.08133v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) has become a dominant architecture for scaling large language models due to their sparse activation mechanism. However, the s

An Automated Survey of Generative Artificial Intelligence: Large Language Models, Architectures, Protocols, and Applications

arXiv:2306.02781v4 Announce Type: replace-cross Abstract: Generative artificial intelligence, and large language models in particular, have emerged as one of the most transformative paradigms in moder

AnchorSplat: Feed-Forward 3D Gaussian Splatting with 3D Geometric Priors

model-releasesarxiv-cs-cv

arXiv:2604.07053v2 Announce Type: replace Abstract: Recent feed-forward Gaussian reconstruction models adopt a pixel-aligned formulation that maps each 2D pixel to a 3D Gaussian, entangling Gaussian r

Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions

arXiv:2604.07277v1 Announce Type: cross Abstract: Online reinforcement learning (RL) serves as an effective method for enhancing the capabilities of Android agents. However, guiding agents to learn th

safetyarxiv-cs-ai

AnomalyVFM -- Transforming Vision Foundation Models into Zero-Shot Anomaly Detectors

model-releasesarxiv-cs-cv

arXiv:2601.20524v2 Announce Type: replace Abstract: Zero-shot anomaly detection aims to detect and localise abnormal regions in the image without access to any in-domain training images. While recent

Assessing the Added Value of Onboard Earth Observation Processing with the IRIDE HEO Service Segment

arXiv:2604.07120v1 Announce Type: cross Abstract: Current operational Earth Observation (EO) services, including the Copernicus Emergency Management Service (CEMS), the European Forest Fire Informatio

agentsarxiv-cs-ai

ASUS UGen300 USB AI Accelerator 8GB for local inference

local-air-stablediffusion

The ASUS UGen300 is a plug-and-play USB AI accelerator featuring a Hailo-10H processor that delivers up to 40 TOPS (INT4) of inference performance and 8GB of dedicated LPDDR4 memory, consuming just...

AtomEval: Atomic Evaluation of Adversarial Claims in Fact Verification

arXiv:2604.07967v1 Announce Type: new Abstract: Adversarial claim rewriting is widely used to test fact-checking systems, but standard metrics fail to capture truth-conditional consistency and often l

researcharxiv-cs-cl

AudioRole: An Audio Dataset for Character Role-Playing in Large Language Models

arXiv:2509.23435v2 Announce Type: replace-cross Abstract: The creation of high-quality multimodal datasets remains fundamental for advancing role-playing capabilities in large language models (LLMs).

safetyarxiv-cs-ai

Auditing Black-Box LLM APIs with a Rank-Based Uniformity Test

arXiv:2506.06975v5 Announce Type: replace-cross Abstract: As API access becomes a primary interface to large language models (LLMs), users often interact with black-box systems that offer little trans

local-aiarxiv-cs-cl

AVGen-Bench: A Task-Driven Benchmark for Multi-Granular Evaluation of Text-to-Audio-Video Generation

arXiv:2604.08540v1 Announce Type: cross Abstract: Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchma

BadImplant: Injection-based Multi-Targeted Graph Backdoor Attack

arXiv:2601.15474v2 Announce Type: replace-cross Abstract: Graph neural network (GNN) have demonstrated exceptional performance in solving critical problems across diverse domains yet remain susceptibl

Tutorials

Balanced Diffusion-Guided Fusion for Multimodal Remote Sensing Classification

arXiv:2509.23310v3 Announce Type: replace Abstract: Deep learning-based techniques for the analysis of multimodal remote sensing data have become popular due to their ability to effectively integrate

tutorialsarxiv-cs-cv

Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA

arXiv:2604.06173v1 Announce Type: cross Abstract: Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory do

Beyond Loss Values: Robust Dynamic Pruning via Loss Trajectory Alignment

arXiv:2604.07306v1 Announce Type: cross Abstract: Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This

safetyarxiv-cs-lg

Beyond Pessimism: Offline Learning in KL-regularized Games

arXiv:2604.06738v1 Announce Type: cross Abstract: We study offline learning in KL-regularized two-player zero-sum games, where policies are optimized under a KL constraint to a fixed reference policy.

safetyarxiv-cs-lg

Beyond the Mean: Modelling Annotation Distributions in Continuous Affect Prediction

arXiv:2604.07198v1 Announce Type: new Abstract: Emotion annotation is inherently subjective and cognitively demanding, producing signals that reflect diverse perceptions across annotators rather than

Bi-Level Optimization for Single Domain Generalization

arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch

BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning

arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN

BLaDA: Bridging Language to Functional Dexterous Actions within 3DGS Fields

arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio

researcharxiv-cs-cv

Blending Human and LLM Expertise to Detect Hallucinations and Omissions in Mental Health Chatbot Responses

arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet

Bridging MRI and PET physiology: Untangling complementarity through orthogonal representations

arXiv:2604.07154v1 Announce Type: cross Abstract: Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modalit

Bridging Time and Space: Decoupled Spatio-Temporal Alignment for Video Grounding

arXiv:2604.08014v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding requires jointly localizing target objects across both temporal and spatial dimensions based on natural language queries

local-aiarxiv-cs-cv

BTC-LLM: Efficient Sub-1-Bit LLM Quantization via Learnable Transformation and Binary Codebook

model-releasesarxiv-cs-cv

arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.

Applications

Build on Replit. Deploy to @databricks Replit can now build secure, enterprise-ready apps on Databricks.

Replit and Databricks have partnered to enable enterprise teams to build and deploy secure, production-grade data and AI applications by combining Replit's AI-powered development environment with D...

applicationsreplit--x

CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data

arXiv:2604.07583v1 Announce Type: new Abstract: Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performanc

Applications

ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding

arXiv:2604.06685v1 Announce Type: cross Abstract: While Vision-Language Models (VLMs) have demonstrated significant potential in chemical visual understanding, current models are predominantly optimiz

applicationsarxiv-cs-ai

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

ClawBench: Can AI Agents Complete Everyday Online Tasks?

arXiv:2604.08523v1 Announce Type: new Abstract: AI agents may be able to automate your inbox, but can they automate other routine aspects of your life? Everyday online tasks offer a realistic yet unso

ClawLess: A Security Model of AI Agents

arXiv:2604.06284v1 Announce Type: cross Abstract: Autonomous AI agents powered by Large Language Models can reason, plan, and execute complex tasks, but their ability to autonomously retrieve informat

agentsarxiv-cs-ai

Clinical Cognition Alignment for Gastrointestinal Diagnosis with Multimodal LLMs

arXiv:2603.20698v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable potential in medical image analysis. However, their application in gastr

local-aiarxiv-cs-cl

Component-Adaptive and Lesion-Level Supervision for Improved Small Structure Segmentation in Brain MRI

arXiv:2604.08015v1 Announce Type: new Abstract: We propose a unified objective function, termed CATMIL, that augments the base segmentation loss with two auxiliary supervision terms operating at diffe

researcharxiv-cs-cv

Concentrated siting of AI data centers drives regional power-system stress under rising global compute demand

arXiv:2604.06198v1 Announce Type: cross Abstract: The rapid rise of generative artificial intelligence (AI) is driving unprecedented growth in global computational demand, placing increasing pressure

local-aiarxiv-cs-ai

ConceptTracer: Interactive Analysis of Concept Saliency and Selectivity in Neural Representations

arXiv:2604.07019v1 Announce Type: cross Abstract: Neural networks deliver impressive predictive performance across a variety of tasks, but they are often opaque in their decision-making processes. Des

ConfusionPrompt: Practical Private Inference for Online Large Language Models

arXiv:2401.00870v5 Announce Type: replace-cross Abstract: State-of-the-art large language models (LLMs) are typically deployed as online services, requiring users to transmit detailed prompts to cloud

local-aiarxiv-cs-ai

ConsistRM: Improving Generative Reward Models via Consistency-Aware Self-Training

arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea

Continuous-Time Dynamics of the Difference-of-Convex Algorithm

arXiv:2604.06926v1 Announce Type: cross Abstract: We study the continuous-time structure of the difference-of-convex algorithm (DCA) for smooth DC decompositions with a strongly convex component. In d

agentsarxiv-cs-lg

Controller Design for Structured State-space Models via Contraction Theory

arXiv:2604.07069v1 Announce Type: cross Abstract: This paper presents an indirect data-driven output feedback controller synthesis for nonlinear systems, leveraging Structured State-space Models (SSMs