Search: “meta”

WARBERT: A Hierarchical BERT-based Model for Web API Recommendation

arXiv:2509.23175v2 Announce Type: replace-cross Abstract: With the rise of Web 2.0 and microservices, the increasing availability of Web APIs has intensified the need for effective recommendation syst

20 Apr 2026

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Weak-Link Optimization for Multi-Agent Reasoning and Collaboration

DGX agent

arXiv:2604.15972v1 Announce Type: new Abstract: LLM-driven multi-agent frameworks address complex reasoning tasks through multi-role collaboration. However, existing approaches often suffer from reaso

agentsarxiv-cs-ai

20 Apr 2026

3D Conditional Image Synthesis of Left Atrial LGE MRI from Composite Semantic Masks

arXiv:2601.04588v2 Announce Type: replace Abstract: Segmentation of the left atrial (LA) wall and endocardium from late gadolinium-enhanced (LGE) MRI is essential for quantifying atrial fibrosis in pa

Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation

arXiv:2601.07338v2 Announce Type: replace Abstract: Large Language Models (LLMs) have significantly advanced Machine Translation (MT), applying them to linguistically complex domains-such as Social Ne

agentsarxiv-cs-cl

C2W-Tune: Cavity-to -Wall Transfer Learning for Thin Atrial Wall Segmentation in 3D Late Gadolinium-enhanced Magnetic Resonance

arXiv:2603.24992v2 Announce Type: replace Abstract: Accurate segmentation of the left atrial (LA) wall in 3D late gadolinium-enhanced MRI (LGE-MRI) is essential for wall thickness mapping and fibrosis

Robustness of Vision Foundation Models to Common Perturbations

arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright

The Acoustic Camouflage Phenomenon: Re-evaluating Speech Features for Financial Risk Prediction

arXiv:2604.14619v1 Announce Type: cross Abstract: In computational paralinguistics, detecting cognitive load and deception from speech signals is a heavily researched domain. Recent efforts have attem

researcharxiv-cs-lg

When Flat Minima Fail: Characterizing INT4 Quantization Collapse After FP32 Convergence

model-releasesarxiv-cs-lg

arXiv:2604.15167v1 Announce Type: new Abstract: Post-training quantization (PTQ) assumes that a well-converged model is a quantization-ready model. We show this assumption fails in a structured, measu

Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments

arXiv:2604.13085v1 Announce Type: new Abstract: Autonomous AI agents operating in dynamic environments face a persistent challenge: acquiring new capabilities without erasing prior knowledge. We prese

agentsarxiv-cs-lg

16 Apr 2026

Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization

arXiv:2601.04442v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) have exhibited strong reasoning capabilities through chain-of-thought mechanisms that generate step-by-st

tutorialsarxiv-cs-cl

16 Apr 2026

Applications

Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents

arXiv:2604.14004v1 Announce Type: cross Abstract: Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization

applicationsarxiv-cs-cl

16 Apr 2026

Applications

A Two-Stage LLM Framework for Accessible and Verified XAI Explanations

arXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib

applicationsarxiv-cs-ai

DyBBT: Dynamic Balance via Bandit-inspired Targeting for Dialog Policy with Cognitive Dual-Systems

arXiv:2509.19695v3 Announce Type: replace-cross Abstract: Task oriented dialog systems often rely on static exploration strategies that do not adapt to dynamic dialog contexts, leading to inefficient

safetyarxiv-cs-ai

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

model-releasesarxiv-cs-lg

arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).

SOLARIS: Speculative Offloading of Latent-bAsed Representation for Inference Scaling

arXiv:2604.12110v1 Announce Type: new Abstract: Recent advances in recommendation scaling laws have led to foundation models of unprecedented complexity. While these models offer superior performance,

researcharxiv-cs-lg

The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery

TimeMark: A Trustworthy Time Watermarking Framework for Exact Generation-Time Recovery from AIGC

arXiv:2604.12216v1 Announce Type: cross Abstract: The widespread use of Large Language Models (LLMs) in text generation has raised increasing concerns about intellectual property disputes. Watermarkin

researcharxiv-cs-cl

When Self-Reference Fails to Close: Matrix-Level Dynamics in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.12128v1 Announce Type: new Abstract: We investigate how self-referential inputs alter the internal matrix dynamics of large language models. Measuring 106 scalar metrics across up to 7 anal

A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

arXiv:2604.10116v1 Announce Type: cross Abstract: Major depressive disorder (MDD) is a prevalent mental disorder associated with complex neurobiological changes that cannot be fully captured using a s

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning

arXiv:2604.11272v1 Announce Type: cross Abstract: Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and th

tutorialsarxiv-cs-ai

Bottleneck Tokens for Unified Multimodal Retrieval

arXiv:2604.11095v1 Announce Type: cross Abstract: Adapting decoder-only multimodal large language models (MLLMs) for unified multimodal retrieval faces two structural gaps. First, existing methods rel

Do Thought Streams Matter? Evaluating Reasoning in Gemini Vision-Language Models for Video Scene Understanding

model-releasesarxiv-cs-cv

arXiv:2604.11177v1 Announce Type: new Abstract: We benchmark how internal reasoning traces, which we call thought streams, affect video scene understanding in vision-language models. Using four config

Evaluating Scene-based In-Situ Item Labeling for Immersive Conversational Recommendation

arXiv:2604.09698v1 Announce Type: cross Abstract: The growing ubiquity of Extended Reality (XR) is driving Conversational Recommendation Systems (CRS) toward visually immersive experiences. We formali

Evolving Many Worlds: Towards Open-Ended Discovery in Petri Dish NCA via Population-Based Training

arXiv:2604.11248v1 Announce Type: cross Abstract: The generation of sustained, open-ended complexity from local interactions remains a fundamental challenge in artificial life. Differentiable multi-ag

agentsarxiv-cs-ai

Local Ai

Fairboard: a quantitative framework for equity assessment of healthcare models

arXiv:2604.09656v1 Announce Type: cross Abstract: Despite there now being more than 1,000 FDA-authorised AI medical devices, formal equity assessments -- whether model performance is uniform across pa

local-aiarxiv-cs-ai

From Scalars to Tensors: Declared Losses Recover Epistemic Distinctions That Neutrosophic Scalars Cannot Express

arXiv:2604.09602v1 Announce Type: new Abstract: Leyva-Vazquez and Smarandache (2025) demonstrated that neutrosophic T/I/F evaluation, where Truth, Indeterminacy, and Falsity are independent dimensions

Graph-Coarsening Approach for the Capacitated Vehicle Routing Problem with Time Windows

arXiv:2510.22329v2 Announce Type: replace Abstract: The Capacitated Vehicle Routing Problem with Time Windows (CVRPTW) is a fundamental NP-hard optimization problem in logistics. Solving large-scale i

Improving Pediatric Emergency Department Triage with Modality Dropout in Late Fusion Multimodal EHR Models

arXiv:2604.09905v1 Announce Type: new Abstract: Emergency department triage relies heavily on both quantitative vital signs and qualitative clinical notes, yet multimodal machine learning models predi

researcharxiv-cs-lg

Physics-Informed Synthetic Dataset and Denoising TIE-Reconstructed Phase Maps in Transient Flows Using Deep Learning

arXiv:2604.10610v1 Announce Type: cross Abstract: High-speed quantitative phase imaging enables non-intrusive visualization of transient compressible gas flows and energetic phenomena. However, phase

Reasoning as Data: Representation-Computation Unity and Its Implementation in a Domain-Algebraic Inference Engine

arXiv:2604.10908v1 Announce Type: new Abstract: Every existing knowledge system separates storage from computation. We show this separation is unnecessary and eliminate it. In a standard triple is_a(A

Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systems

arXiv:2604.09963v1 Announce Type: cross Abstract: Microreboot enables fast recovery by restarting only the failing component, but in modern microservices naive restarts are unsafe: dense dependencies

safetyarxiv-cs-ai

Reinforced Generation of Combinatorial Structures: Ramsey Numbers

arXiv:2603.09172v4 Announce Type: replace-cross Abstract: We present improved lower bounds for seven classical Ramsey numbers: mathbf{R}(3, 13) is increased from 60 to 61, mathbf{R}(3, 18) from 99 to

agentsarxiv-cs-ai

Semantic-Space Exploration and Exploitation in RLVR for LLM Reasoning

arXiv:2509.23808v4 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) for LLM reasoning is often framed as balancing exploration and exploitation in action sp

researcharxiv-cs-cl

TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance

arXiv:2509.26627v2 Announce Type: replace Abstract: Designing dense rewards is crucial for reinforcement learning (RL), yet in robotics it often demands extensive manual effort and lacks scalability.

tutorialsarxiv-cs-ai

Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations

model-releasesarxiv-cs-cl

arXiv:2604.09625v1 Announce Type: new Abstract: We study whether large-scale unlabelled web data and LLM-based synthetic annotations can improve multilingual hate speech detection. Starting from texts

Training Deep Visual Networks Beyond Loss and Accuracy Through a Dynamical Systems Approach

arXiv:2604.09716v1 Announce Type: cross Abstract: Deep visual recognition models are usually trained and evaluated using metrics such as loss and accuracy. While these measures show whether a model is

Training-Free Cross-Lingual Dysarthria Severity Assessment via Phonological Subspace Analysis in Self-Supervised Speech Representations

arXiv:2604.10123v1 Announce Type: new Abstract: Dysarthric speech severity assessment typically requires trained clinicians or supervised models built from labelled pathological speech, limiting scala

safetyarxiv-cs-cl

Zero-shot World Models Are Developmentally Efficient Learners

arXiv:2604.10333v1 Announce Type: new Abstract: Young children demonstrate early abilities to understand their physical world, estimating depth, motion, object coherence, interactions, and many other

Automatic Self-supervised Learning for Social Recommendations

arXiv:2412.18735v3 Announce Type: replace-cross Abstract: In recent years, researchers have leveraged social relations to enhance recommendation performance. However, most existing social recommendati

tutorialsarxiv-cs-lg

Local Ai

Mapping generative AI use in the human brain: divergent neural, academic, and mental health profiles of functional versus socio emotional AI use

arXiv:2604.08594v1 Announce Type: cross Abstract: The widespread adoption of generative artificial intelligence conversational agents (AICAs) among university students constitutes a novel cognitive so

local-aiarxiv-cs-ai

Out-of-the-box: Black-box Causal Attacks on Object Detectors

arXiv:2512.03730v2 Announce Type: replace-cross Abstract: Adversarial perturbations are a useful way to expose vulnerabilities in object detectors. Existing perturbation methods are frequently white-b

QARIMA: A Quantum Approach To Classical Time Series Analysis

arXiv:2604.08277v2 Announce Type: replace-cross Abstract: We present a quantum-inspired ARIMA methodology that integrates quantum-assisted lag discovery with fixed-configuration variational quantum ci

AgentCity: Constitutional Governance for Autonomous Agent Economies via Separation of Power

arXiv:2604.07007v1 Announce Type: cross Abstract: Autonomous AI agents are beginning to operate across organizational boundaries on the open internet -- discovering, transacting with, and delegating t

safetyarxiv-cs-ai

An Agentic Evaluation Architecture for Historical Bias Detection in Educational Textbooks

arXiv:2604.07883v1 Announce Type: cross Abstract: History textbooks often contain implicit biases, nationalist framing, and selective omissions that are difficult to audit at scale. We propose an agen

safetyarxiv-cs-cl

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu

Computer Environments Elicit General Agentic Intelligence in LLMs

arXiv:2601.16206v3 Announce Type: replace-cross Abstract: Agentic intelligence in large language models (LLMs) requires not only model intrinsic capabilities but also interactions with external enviro

agentsarxiv-cs-ai

From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning

arXiv:2604.06262v1 Announce Type: cross Abstract: Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-con

Lost in Cultural Translation: Do LLMs Struggle with Math Across Cultural Contexts?

arXiv:2503.18018v2 Announce Type: replace Abstract: We demonstrate that large language models' (LLMs) mathematical reasoning is culturally sensitive: testing 14 models from Anthropic, OpenAI, Google,