Search: “models”

The Coupling Tax: How Shared Token Budgets Undermine Visible Chain-of-Thought Under Fixed Output Limits

arXiv:2605.07686v1 Announce Type: new Abstract: Chain-of-thought reasoning is often treated as a monotone way to improve language-model accuracy by letting a model think longer. We identify a counterv

11 May 2026

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Model Releases

The Single-File Test: A Longitudinal Public-Interface Evaluation of First-Output LLM Web Generation with Social Reach Tracking

DGX agent

arXiv:2605.06707v1 Announce Type: cross Abstract: This paper presents an eight-week observational comparison of 68 single-file HTML generations collected across 17 public experiments in the 'HTML AI B

model-releasesarxiv-cs-ai

11 May 2026

TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models

arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict

safetyarxiv-cs-lg

11 May 2026

Training-Free Multimodal Large Language Model Orchestration

arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia

safetyarxiv-cs-cl

11 May 2026

EdgeRazor: A Lightweight Framework for Large Language Models via Mixed-Precision Quantization-Aware Distillation

arXiv:2605.04062v1 Announce Type: new Abstract: Recent years have witnessed an increasing interest in deploying LLMs on resource-constrained devices, among which quantization has emerged as a promisin

How Does the Lagrangian Guide Safe Reinforcement Learning through Diffusion Models?

arXiv:2602.02924v2 Announce Type: replace Abstract: Diffusion policy sampling enables reinforcement learning (RL) to represent multimodal action distributions beyond suboptimal unimodal Gaussian polic

safetyarxiv-cs-lg

Local Ai

Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning

arXiv:2605.05009v1 Announce Type: new Abstract: Many decentralized distillation methods are designed around training-time coordination, yet deploy each node in isolation even when more capable neighbo

local-aiarxiv-cs-lg

MAD-BA: 3D LiDAR Bundle Adjustment -- from Uncertainty Modelling to Structure Optimization

arXiv:2501.03972v2 Announce Type: replace Abstract: The joint optimization of sensor poses and 3D structure is fundamental for state estimation in robotics and related fields. Current LiDAR systems of

researcharxiv-cs-ro

Local Ai

MixINN: Accelerating Plant Breeding by Combining Mixed Models and Deep Learning for Interaction Prediction

arXiv:2605.04744v1 Announce Type: new Abstract: Plant breeding underpins global food security through incremental, accumulating improvements in crop yield, quality and sustainability, achieved via rep

local-aiarxiv-cs-lg

Model synthesis and identifiability analysis of stiff chemical reaction systems with inVAErt networks

arXiv:2605.04134v1 Announce Type: new Abstract: We consider the problem of learning data-driven replicas for stiff systems of ordinary differential equations arising in chemical kinetics that can be e

MRI-Eval: A Tiered Benchmark for Evaluating LLM Performance on MRI Physics and GE Scanner Operations Knowledge

arXiv:2605.05175v1 Announce Type: cross Abstract: Background: Existing MRI LLM benchmarks rely mainly on review-book multiple-choice questions, where top proprietary models already score highly, limit

Prompt-Anchored Vision-Text Distillation for Lifelong Person Re-identification

arXiv:2605.05027v1 Announce Type: new Abstract: Lifelong person re-identification (LReID) aims to train a generalizable model with sequentially collected data. However, such models often suffer from s

Reduced-order Neural Modeling with Differentiable Simulation for High-Detail Tactile Perception

arXiv:2605.05053v1 Announce Type: cross Abstract: Tactile perception is key to dexterous manipulation, yet simulating high-resolution elastomer deformation remains computationally prohibitive. Finite

Skill Neologisms: Towards Skill-based Continual Learning

arXiv:2605.04970v1 Announce Type: new Abstract: Modern LLMs show mastery over an ever-growing range of skills, as well as the ability to compose them flexibly. However, extending model capabilities to

TabEmbed: Benchmarking and Learning Generalist Embeddings for Tabular Understanding

arXiv:2605.04962v1 Announce Type: new Abstract: Foundation models have established unified representations for natural language processing, yet this paradigm remains largely unexplored for tabular dat

TSCG: Deterministic Tool-Schema Compilation for Agentic LLM Deployments

arXiv:2605.04107v1 Announce Type: cross Abstract: Production agent frameworks (OpenAI Function Calling, Anthropic Tool Use, MCP) transmit tool schemas as JSON, a format designed for machine parsing, n

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions

arXiv:2605.04209v1 Announce Type: cross Abstract: We present Sparse Backdoor, a supply-chain attack that plants a provably undetectable backdoor in pre-trained image classifiers, including convolution

Vision-EKIPL: External Knowledge-Infused Policy Learning for Visual Reasoning

arXiv:2506.06856v3 Announce Type: replace Abstract: Visual reasoning is crucial for understanding complex multimodal data and advancing Artificial General Intelligence. Existing methods enhance the re

12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation

model-releasesarxiv-cs-ai

arXiv:2605.01986v1 Announce Type: new Abstract: What if the twelve jurors of Sidney Lumet's 12 Angry Men (1957) were not men, but large language models? Would the one juror who disagrees still be able

BiMind: A Dual-Head Reasoning Model with Attention-Geometry Adapter for Incorrect Information Detection

arXiv:2604.06022v2 Announce Type: replace Abstract: Incorrect information poses significant challenges by disrupting content veracity and integrity, yet most detection approaches struggle to jointly b

researcharxiv-cs-cl

DeRelayL: Sustainable Decentralized Relay Learning

arXiv:2605.02935v1 Announce Type: new Abstract: In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale m

DINO Soars: DINOv3 for Open-Vocabulary Semantic Segmentation of Remote Sensing Imagery

arXiv:2605.03175v1 Announce Type: new Abstract: The remote sensing (RS) domain suffers from a lack of densely labeled datasets, which are costly to obtain. Thus, models that can segment RS imagery wel

Discovering Reinforcement Learning Interfaces with Large Language Models

arXiv:2605.03408v1 Announce Type: new Abstract: Reinforcement learning systems rely on environment interfaces that specify observations and reward functions, yet constructing these interfaces for new

safetyarxiv-cs-lg

Dynamic Vine Copulas: Detecting and Quantifying Time-Varying Higher-Order Interactions

arXiv:2605.03061v1 Announce Type: cross Abstract: Time varying dependence is often modeled through dynamic correlations or Gaussian graphical models, yet many multivariate systems change through tail

Efficient Deconvolution in Populational Inverse Problems

arXiv:2505.19841v2 Announce Type: replace-cross Abstract: This work is focussed on the inversion task of inferring the distribution over parameters of interest leading to multiple sets of observations

Tutorials

Enhance the after-discharge mortality rate prediction via learning from the medical notes

arXiv:2605.03560v1 Announce Type: new Abstract: With the increase of the Electronic Health Records (EHR) data, more and more researchers are developing machine learning models to learn from the medica

tutorialsarxiv-cs-lg

Applications

Free Decompression with Algebraic Spectral Curves

arXiv:2605.03634v1 Announce Type: cross Abstract: Tools from random matrix theory have become central to deep learning theory, using spectral information to provide mechanisms for modeling generalizat

applicationsarxiv-cs-lg

Iterative Finetuning is Mostly Idempotent

arXiv:2605.01130v1 Announce Type: new Abstract: If a model has some behavioral tendency, such as sycophancy or misalignment, and it is trained on its own outputs, will the tendency be amplified in the

researcharxiv-cs-ai

LitVISTA: A Benchmark for Narrative Orchestration in Literary Text

arXiv:2601.06445v2 Announce Type: replace Abstract: Computational narrative analysis aims to capture rhythm, tension, and emotional dynamics in literary texts. Existing large language models can gener

On Verbalized Confidence Scores for LLMs

arXiv:2412.14737v2 Announce Type: replace Abstract: The rise of large language models (LLMs) and their tight integration into our daily life make it essential to dedicate efforts towards their trustwo

Reasoning-Guided Grounding: Elevating Video Anomaly Detection through Multimodal Large Language Models

arXiv:2605.02912v1 Announce Type: new Abstract: Video Anomaly Detection (VAD) has traditionally been framed as binary classification or outlier detection, providing neither interpretable reasoning nor

Toward Generative Quantum Utility via Correlation-Complexity Map

arXiv:2603.06440v2 Announce Type: replace Abstract: We study a practical question in generative quantum machine learning: given a classical dataset, can we determine, before training, whether it is we

Application Research of a Deep Learning Model Integrating CycleGAN and YOLO in PCB Infrared Defect Detection

arXiv:2601.00237v2 Announce Type: replace Abstract: This paper addresses the critical bottleneck of infrared (IR) data scarcity in Printed Circuit Board (PCB) defect detection by proposing a cross-mod

Beyond Perceptual Shortcuts: Causal-Inspired Debiasing Optimization for Generalizable Video Reasoning in Lightweight MLLMs

arXiv:2605.01324v1 Announce Type: new Abstract: Although reinforcement learning (RL) has significantly advanced reasoning capabilities in large multimodal language models (MLLMs), its efficacy remains

safetyarxiv-cs-cv

Applications

CleverCatch: A Knowledge-Guided Weak Supervision Model for Fraud Detection

arXiv:2510.13205v3 Announce Type: replace Abstract: Healthcare fraud detection remains a critical challenge due to limited availability of labeled data, constantly evolving fraud tactics, and the high

applicationsarxiv-cs-lg

Hardware

Effective Capacitance Modeling Using Graph Neural Networks

arXiv:2507.03787v2 Announce Type: replace Abstract: Static timing analysis is a crucial stage in the VLSI design flow that verifies the timing correctness of circuits. Timing analysis depends on the p

hardwarearxiv-cs-lg

Enhanced LLM Reasoning by Optimizing Reward Functions with Search-Driven Reinforcement Learning

arXiv:2605.02073v1 Announce Type: new Abstract: Mathematical reasoning is a key benchmark for large language models. Reinforcement learning is a standard post-training mechanism for improving the reas

Improving Model Safety by Targeted Error Correction

arXiv:2605.02544v1 Announce Type: cross Abstract: The widespread adoption of machine learning in critical applications demands techniques to mitigate high-consequence errors. Our method utilizes a dua

safetyarxiv-cs-cv

Latent Space Probing for Adult Content Detection in Video Generative Models

arXiv:2605.00874v1 Announce Type: new Abstract: The rapid proliferation of AI-powered video generation systems has introduced significant challenges in content moderation, particularly with respect to

MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio

arXiv:2605.00969v1 Announce Type: cross Abstract: We present MedMosaic, a medical audio question-answering dataset designed to benchmark language and audio reasoning models under realistic clinical co

PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning

arXiv:2605.01759v1 Announce Type: new Abstract: Scene-level point cloud self-supervised learning (PC-SSL) has demonstrated potential in enhancing the generalization capability of 3D vision models. Des

Pruning Federated Models through Loss Landscape Analysis and Client Agreement Scoring

arXiv:2405.10271v4 Announce Type: replace Abstract: The practical deployment of Federated Learning (FL) on resource-constrained devices is fundamentally limited by the high cost of training large mode

Robust Adaptive Predictive Control for Hook-Based Aerial Transportation Between Moving Platforms

model-releasesarxiv-cs-ro

arXiv:2605.02370v1 Announce Type: new Abstract: This paper presents a novel model predictive control (MPC) approach for autonomous pick-and-place between moving platforms with a hook-equipped aerial m

Sharpness-Aware Pretraining Mitigates Catastrophic Forgetting

arXiv:2605.02105v1 Announce Type: cross Abstract: Pretraining optimizers are tuned to produce the strongest possible base model, on the assumption that a stronger starting point yields a stronger mode

TIME: Temporally Intelligent Meta-reasoning Engine for Context-Triggered Explicit Reasoning

arXiv:2601.05300v2 Announce Type: replace-cross Abstract: Reasoning-oriented language models typically expose explicit reasoning as a long, front-loaded chain of 'thinking' tokens before the main outp

TRACED: In vivo imaging of extracellular intrinsic diffusivity, tortuosity, cell size distribution and cell density in human glioma patients

arXiv:2605.02615v1 Announce Type: cross Abstract: The lack of analytical models describing diffusion time dependence at intermediate time scales in complex tissue microstructure limits the accurate qu

Local Ai

A Comparative Analysis of Machine Learning Models for Intrusion Detection in Intelligent Transport Systems

arXiv:2605.00279v1 Announce Type: cross Abstract: AI-powered edge computing security is moving Intelligent Transportation Systems (ITS) from passive, rule-based protections to proactive, smart, zero-t

local-aiarxiv-cs-lg

4 May 2026

Applications

Diffusion Models are Secretly Zero-Shot 3DGS Harmonizers