Search: “models”

arXiv:2605.04074v1 Announce Type: new Abstract: AI data centers experience rapid fluctuations in power demand due to the heterogeneity of computational tasks that they have to support. For example, th

hardwarearxiv-cs-lg

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Advancing Aesthetic Image Generation via Composition Transfer

DGX agent

arXiv:2605.04609v1 Announce Type: new Abstract: Composition is a cornerstone of visual aesthetics, influencing the appeal of an image. While its principles operate independently of specific content, i

researcharxiv-cs-cv

7 May 2026

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2605.05155v1 Announce Type: new Abstract: As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important

Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning

arXiv:2602.19041v2 Announce Type: replace Abstract: A recurring challenge in preference fine-tuning (PFT) is handling extit{intransitive} (i.e., cyclic) preferences. Intransitive preferences often ste

Closed-Loop Vision-Language Planning for Multi-Agent Coordination

arXiv:2502.10148v3 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) struggles with sample efficiency, interpretability, and generalization. While Large Language M

Direct Product Flow Matching: Decoupling Radial and Angular Dynamics for Few-Shot Adaptation

arXiv:2605.05054v1 Announce Type: new Abstract: Recent flow matching (FM) methods improve the few-shot adaptation of vision-language models, by modeling cross-modal alignment as a continuous multi-ste

safetyarxiv-cs-cv

Evaluating Semantic Fragility in Text-to-Audio Generation Systems Under Controlled Prompt Perturbations

arXiv:2603.13824v2 Announce Type: replace-cross Abstract: Recent advances in text-to-audio generation enable models to translate natural-language descriptions into diverse musical output. However, the

safetyarxiv-cs-ai

FAAST: Forward-Only Associative Learning via Closed-Form Fast Weights for Test-Time Supervised Adaptation

arXiv:2605.04651v1 Announce Type: cross Abstract: Adapting pretrained models typically involves a trade-off between the high training costs of backpropagation and the heavy inference overhead of memor

researcharxiv-cs-cl

From Priors to Perception: Grounding Video-LLMs in Physical Reality

arXiv:2605.04515v1 Announce Type: new Abstract: While Video Large Language Models (Video-LLMs) excel in general understanding, they exhibit systematic deficits in fine-grained physical reasoning. Exis

researcharxiv-cs-cv

Heterogeneous Ordinal Structure Learning with Bayesian Nonparametric Complexity Discovery

arXiv:2605.04191v1 Announce Type: cross Abstract: Public attitudes toward artificial intelligence are heterogeneous, ordinally measured, and poorly captured by any single dependency graph. Existing or

Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation

arXiv:2605.05125v1 Announce Type: new Abstract: Target trial emulation (TTE) enables causal questions to be studied with observational data when randomized controlled trials (RCTs) are infeasible. Yet

Jordan-RoPE: Non-Semisimple Relative Positional Encoding via Complex Jordan Blocks

model-releasesarxiv-cs-cl

arXiv:2605.04217v1 Announce Type: cross Abstract: Relative positional encodings determine which functions of query-key lag can enter the primitive attention logit. RoPE supplies a rotary phase, while

LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems

arXiv:2605.04323v1 Announce Type: new Abstract: Understanding soil is fundamental to agriculture, carbon cycling, and environmental sustainability, yet progress is limited by fragmented and heterogene

Mitigating Label Shift in Tabular In-Context Learning via Test-Time Posterior Adjustment

arXiv:2605.04363v1 Announce Type: new Abstract: TabPFN has recently gained attention as a foundation model for tabular datasets, achieving strong performance by leveraging in-context learning on synth

researcharxiv-cs-lg

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

Applications

Rethinking Convolutional Networks for Attribute-Aware Sequential Recommendation

arXiv:2605.04723v1 Announce Type: cross Abstract: Attribute-aware sequential recommendation entails predicting the next item a user will interact with based on a chronologically ordered history of pas

applicationsarxiv-cs-lg

SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression

arXiv:2605.04560v1 Announce Type: new Abstract: Perceptual image compression focuses on preserving high visual quality under low-bitrate constraints. Most existing approaches to perceptual compression

researcharxiv-cs-cv

Sharp Capacity Thresholds in Linear Associative Memory: From Winner-Take-All to Listwise Retrieval

arXiv:2605.05189v1 Announce Type: cross Abstract: How many key-value associations can a dimes d linear memory store? We show that the answer depends not only on the d^2 degrees of freedom in the memor

Local Ai

Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control

arXiv:2605.04468v1 Announce Type: cross Abstract: Post-training large language models (LLMs) often suffers from catastrophic forgetting, where improvements on a target objective degrade previously acq

local-aiarxiv-cs-cl

Stage Light is Sequence^2: Multi-Light Control via Imitation Learning

arXiv:2605.03660v1 Announce Type: cross Abstract: Music-inspired Automatic Stage Lighting Control (ASLC) has gained increasing attention in recent years due to the substantial time and financial costs

The Predictive-Causal Gap: An Impossibility Theorem and Large-Scale Neural Evidence

arXiv:2605.05029v1 Announce Type: new Abstract: We report a systematic failure mode in predictive representation learning. Across 2695 neural network configurations trained to predict linear-Gaussian

UI2Code^N: UI-to-Code Generation as Interactive Visual Optimization

arXiv:2511.08195v3 Announce Type: replace Abstract: UI-to-code aims to translate UI screenshots into executable front-end code. Despite progress with vision-language models (VLMs), most existing metho

safetyarxiv-cs-cv

VCBench: Benchmarking LLMs in Venture Capital

arXiv:2509.14448v2 Announce Type: replace Abstract: Benchmarks such as SWE-bench and ARC-AGI demonstrate how shared datasets accelerate progress toward artificial general intelligence (AGI). We introd

What Happens Inside Agent Memory? Circuit Analysis from Emergence to Diagnosis

arXiv:2605.03354v1 Announce Type: new Abstract: Agent memory failures are silent: an LLM-based agent can produce a fluent response even when it fails to extract, retain, or retrieve the information ne

Agents

What You Think is What You See: Driving Exploration in VLM Agents via Visual-Linguistic Curiosity

arXiv:2605.03782v1 Announce Type: new Abstract: To navigate partially observable visual environments, recent VLM agents increasingly internalize world modeling capabilities into their policies via exp

agentsarxiv-cs-ai

A Framework for Exploring and Disentangling Intersectional Bias: A Case Study in Fetal Ultrasound

model-releasesarxiv-cs-cv

arXiv:2605.02942v1 Announce Type: cross Abstract: Bias in medical AI is often framed as a problem of representation. However, in image-based tasks such as fetal ultrasound, performance disparities can

ABD: Default Exception Abduction in Finite First Order Worlds

arXiv:2602.18843v3 Announce Type: replace Abstract: We introduce ABD, a benchmark for default-exception abduction over finite first-order worlds. Given a background theory with an abnormality predicat

AcademiClaw: When Students Set Challenges for AI Agents

arXiv:2605.02661v1 Announce Type: new Abstract: Benchmarks within the OpenClaw ecosystem have thus far evaluated exclusively assistant-level tasks, leaving the academic-level capabilities of OpenClaw

AI Agents for Inventory Control: Human-LLM-OR Complementarity

arXiv:2602.12631v2 Announce Type: replace-cross Abstract: Inventory control is a fundamental operations problem in which ordering decisions are traditionally guided by theoretically grounded operation

Analysis and Explainability of LLMs Via Evolutionary Methods

arXiv:2605.02930v1 Announce Type: cross Abstract: Evolutionary methods have long been useful for analysis and explanation in genetics, biology, ecology, and related fields. In this work, we extend the

researcharxiv-cs-lg

Benchmarking Logistic Regression, SVM, Naive Bayes, and IndoBERT Fine-Tuning for Sentiment Analysis on Indonesian Product Reviews

arXiv:2605.03439v1 Announce Type: new Abstract: The exponential growth of e-commerce platforms in Indonesia has generated a massive volume of user-generated product reviews. Analyzing the sentiment of

researcharxiv-cs-cl

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

arXiv:2605.03148v1 Announce Type: new Abstract: Reliable wildfire spread prediction is vital for risk-aware emergency planning, yet most deep learning models lack principled uncertainty quantification

researcharxiv-cs-cv

Capturing reduced-order quantum many-body dynamics out of equilibrium via neural ordinary differential equations

arXiv:2512.13913v3 Announce Type: replace Abstract: Out-of-equilibrium quantum many-body systems exhibit rapid correlation buildup that underlies many emerging phenomena. Exact wave-function methods t

Causal Software Engineering: A Vision and Roadmap

arXiv:2605.02454v1 Announce Type: cross Abstract: Software engineering increasingly involves making high-stakes decisions under uncertainty, using signals from code, field data, and socio-technical pr

Local Ai

Correct Is Not Enough: Training Reasoning Planners with Executor-Grounded Rewards

arXiv:2605.03862v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards has become a common way to improve explicit reasoning in large language models, but final-answer correc

local-aiarxiv-cs-cl

DataClaw: A Process-Oriented Agent Benchmark for Exploratory Real-World Data Analysis

arXiv:2605.02503v1 Announce Type: new Abstract: Evaluating autonomous data analysis agents requires testing their ability to perform exploratory analysis in underexplored data environments. However, m

DataEvolver: Let Your Data Build and Improve Itself via Goal-Driven Loop Agents

arXiv:2605.01789v1 Announce Type: new Abstract: Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a s

Detecting Stealth Sycophancy in Mental-Health Dialogue with Dynamic Emotional Signature Graphs

model-releasesarxiv-cs-cl

arXiv:2605.03472v1 Announce Type: new Abstract: As conversational AI therapists are increasingly used in psychological support settings, reliable offline evaluation of therapeutic response quality rem

Do LLMs have core beliefs?

arXiv:2605.03255v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has sparked debate about whether these systems exhibit human-level cognition. In this debate, little attention

researcharxiv-cs-lg

Donor-Aware scRNA-seq Benchmarks for IBD Classification

arXiv:2605.03281v1 Announce Type: cross Abstract: Donor-level disease classification from single-cell RNA sequencing (scRNA-seq) requires strict donor-aware cross-validation: naive pipelines that spli

Epistemic Reject Option Prediction

arXiv:2511.04855v2 Announce Type: replace Abstract: In high-stakes applications, predictive models must not only produce accurate predictions but also quantify and communicate their uncertainty. Rejec

researcharxiv-cs-ai

Feasibility-aware Hybrid Control for Motion Planning under Signal Temporal Logics

arXiv:2605.03662v1 Announce Type: new Abstract: In this work, a novel method for planar task and motion planning based on hybrid modeling is proposed. By virtue of a discrete variable which models loc

researcharxiv-cs-ro

First-Order Efficiency for Probabilistic Value Estimation via A Statistical Viewpoint

arXiv:2605.02827v1 Announce Type: new Abstract: Probabilistic values, including Shapley values and semivalues, provide a model-agnostic framework to attribute the behavior of a black-box model to data

researcharxiv-cs-ai

From Static Analysis to Audience Dissemination: A Training-Free Multimodal Controversy Detection Multi-Agent Framework

arXiv:2605.02939v1 Announce Type: new Abstract: Multimodal controversy detection (MCD) identifies controversial content in videos and their associated user comments, to support risk management for soc

Graph Reconstruction from Differentially Private GNN Explanations

arXiv:2605.03388v1 Announce Type: new Abstract: Regulatory frameworks such as GDPR increasingly require that ML predictions be accompanied by post-hoc explanations, even when raw data and trained mode

NeuroState-Bench: A Human-Calibrated Benchmark for Commitment Integrity in LLM Agent Profiles

arXiv:2605.01847v1 Announce Type: new Abstract: Outcome-only evaluation under-specifies whether an evaluated agent profile preserves the commitments required to solve a multi-turn task coherently. Neu

Not that Groove: Zero-Shot Symbolic Music Editing

model-releasesarxiv-cs-cl

arXiv:2505.08203v2 Announce Type: replace-cross Abstract: While recent advancements in AI music generation have predominantly focused on direct audio synthesis, these systems suffer from inherent rigi

On Surprising Effects of Risk-Aware Domain Randomization for Contact-Rich Sampling-based Predictive Control

arXiv:2605.03290v1 Announce Type: new Abstract: Domain randomization (DR) is widely used in policy learning to improve robustness to modeling error, but remains underexplored in contact-rich sampling-

safetyarxiv-cs-ro