Search: “models”

METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models

arXiv:2604.11502v1 Announce Type: cross Abstract: Contextual causal reasoning is a critical yet challenging capability for Large Language Models (LLMs). Existing benchmarks, however, often evaluate th

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MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models

DGX agent

arXiv:2604.10971v1 Announce Type: cross Abstract: In the progress of industrial anomaly detection, general anomaly detection (GAD) is an emerging trend and also the ultimate goal. Unlike the conventio

model-releasesarxiv-cs-ai

14 Apr 2026

OccuBench: Evaluating AI Agents on Real-World Professional Tasks via Language World Models

arXiv:2604.10866v1 Announce Type: new Abstract: AI agents are expected to perform professional work across hundreds of occupational domains (from emergency department triage to nuclear reactor safety

Physics and causally constrained discrete-time neural models of turbulent dynamical systems

arXiv:2602.13847v3 Announce Type: replace-cross Abstract: We present a framework for constructing physics and causally constrained neural models of turbulent dynamical systems from data. We first form

PoreDiT: A Scalable Generative Model for Large-Scale Digital Rock Reconstruction

arXiv:2604.10171v1 Announce Type: new Abstract: This manuscript presents PoreDiT, a novel generative model designed for high-efficiency digital rock reconstruction at gigavoxel scales. Addressing the

Resource Consumption Threats in Large Language Models

arXiv:2603.16068v3 Announce Type: replace-cross Abstract: Given limited and costly computational infrastructure, resource efficiency is a key requirement for large language models (LLMs). Efficient LL

Rethinking the Diffusion Model from a Langevin Perspective

arXiv:2604.10465v1 Announce Type: cross Abstract: Diffusion models are often introduced from multiple perspectives, such as VAEs, score matching, or flow matching, accompanied by dense and technically

SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors

arXiv:2510.17516v4 Announce Type: replace-cross Abstract: Large language model (LLM) simulations of human behavior have the potential to revolutionize the social and behavioral sciences, if and only i

Too Nice to Tell the Truth: Quantifying Agreeableness-Driven Sycophancy in Role-Playing Language Models

arXiv:2604.10733v1 Announce Type: cross Abstract: Large language models increasingly serve as conversational agents that adopt personas and role-play characters at user request. This capability, while

TraversalBench: Challenging Paths to Follow for Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2604.10999v1 Announce Type: new Abstract: Vision-language models (VLMs) perform strongly on many multimodal benchmarks. However, the ability to follow complex visual paths -- a task that human o

Vision-Language-Action Model, Robustness, Multi-modal Learning, Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2604.10055v1 Announce Type: new Abstract: Despite their strong performance in embodied tasks, recent Vision-Language-Action (VLA) models remain highly fragile under multimodal perturbations, whe

Your Model Diversity, Not Method, Determines Reasoning Strategy

arXiv:2604.10827v1 Announce Type: new Abstract: Compute scaling for LLM reasoning requires allocating budget between exploring solution approaches (breadth) and refining promising solutions (depth). M

Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts

arXiv:2604.09364v1 Announce Type: cross Abstract: When a Vision-Language Model (VLM) sees a blue banana and answers 'yellow', is the problem of perception or arbitration? We explore the question in te

researcharxiv-cs-cl

CONDESION-BENCH: Conditional Decision-Making of Large Language Models in Compositional Action Space

arXiv:2604.09029v1 Announce Type: cross Abstract: Large language models have been widely explored as decision-support tools in high-stakes domains due to their contextual understanding and reasoning c

From Dispersion to Attraction: Spectral Dynamics of Hallucination Across Whisper Model Scales

arXiv:2604.08591v1 Announce Type: cross Abstract: Hallucinations in large ASR models present a critical safety risk. In this work, we propose the extit{Spectral Sensitivity Theorem}, which predicts a

safetyarxiv-cs-ai

From Reasoning to Agentic: Credit Assignment in Reinforcement Learning for Large Language Models

arXiv:2604.09459v1 Announce Type: new Abstract: Reinforcement learning (RL) for large language models (LLMs) increasingly relies on sparse, outcome-level rewards -- yet determining which actions withi

Medical Reasoning with Large Language Models: A Survey and MR-Bench

arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor

No Single Best Model for Diversity: Learning a Router for Sample Diversity

arXiv:2604.02319v2 Announce Type: replace Abstract: When posed with prompts that permit a large number of valid answers, comprehensively generating them is the first step towards satisfying a wide ran

researcharxiv-cs-cl

RADSeg: Unleashing Parameter and Compute Efficient Zero-Shot Open-Vocabulary Segmentation Using Agglomerative Models

model-releasesarxiv-cs-cv

arXiv:2511.19704v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) underpins many vision and robotics tasks that require generalizable semantic understanding. Existing ap

Tutorials

SkillFactory: Self-Distillation For Learning Cognitive Behaviors

arXiv:2512.04072v2 Announce Type: replace-cross Abstract: Reasoning models leveraging long chains of thought employ various cognitive skills, such as verification of their answers, backtracking, retry

tutorialsarxiv-cs-ai

Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models

arXiv:2604.08815v1 Announce Type: new Abstract: Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-re

safetyarxiv-cs-cv

Beyond Mamba: Enhancing State-space Models with Deformable Dilated Convolutions for Multi-scale Traffic Object Detection

model-releasesarxiv-cs-cv

arXiv:2604.08038v1 Announce Type: new Abstract: In a real-world traffic scenario, varying-scale objects are usually distributed in a cluttered background, which poses great challenges to accurate dete

Code Sharing In Prediction Model Research: A Scoping Review

arXiv:2604.06212v1 Announce Type: cross Abstract: Analytical code is essential for reproducing diagnostic and prognostic prediction model research, yet code availability in the published literature re

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

Tutorials

DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

arXiv:2306.14685v5 Announce Type: replace-cross Abstract: We demonstrate that pre-trained text-to-image diffusion models, despite being trained on raster images, possess a remarkable capacity to guide

tutorialsarxiv-cs-ai

Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing

arXiv:2509.01986v4 Announce Type: replace-cross Abstract: In recent years, integrating multimodal understanding and generation into a single unified model has emerged as a promising paradigm. While th

E2Edev: Benchmarking Large Language Models in End-to-End Software Development Task

arXiv:2510.14509v3 Announce Type: replace-cross Abstract: The rapid advancement in large language models (LLMs) has demonstrated significant potential in End-to-End Software Development (E2ESD). Howev

Local Ai

From Synthetic Data to Real Restorations: Diffusion Model for Patient-specific Dental Crown Completion

arXiv:2603.26588v2 Announce Type: replace-cross Abstract: We present ToothCraft, a diffusion-based model for the contextual generation of tooth crowns, trained on artificially created incomplete teeth

local-aiarxiv-cs-lg

Guardian-as-an-Advisor: Advancing Next-Generation Guardian Models for Trustworthy LLMs

arXiv:2604.07655v1 Announce Type: cross Abstract: Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yield

safetyarxiv-cs-cl

Hardware

HAWK: Head Importance-Aware Visual Token Pruning in Multimodal Models

arXiv:2604.07812v1 Announce Type: new Abstract: In multimodal large language models (MLLMs), the surge of visual tokens significantly increases the inference time and computational overhead, making th

hardwarearxiv-cs-cv

How Independent are Large Language Models? A Statistical Framework for Auditing Behavioral Entanglement and Reweighting Verifier Ensembles

arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra

safetyarxiv-cs-cl

HST-HGN: Heterogeneous Spatial-Temporal Hypergraph Networks with Bidirectional State Space Models for Global Fatigue Assessment

arXiv:2604.08435v1 Announce Type: new Abstract: It remains challenging to assess driver fatigue from untrimmed videos under constrained computational budgets, due to the difficulty of modeling long-ra

researcharxiv-cs-cv

Interventional Time Series Priors for Causal Foundation Models

arXiv:2603.11090v2 Announce Type: replace Abstract: Prior-data fitted networks (PFNs) have emerged as powerful foundation models for tabular causal inference, yet their extension to time series remain

Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling

model-releasesarxiv-cs-lg

arXiv:2508.05423v2 Announce Type: replace Abstract: Although artificial neural networks are often described as brain-inspired, their representations typically rely on continuous activations, such as t

Not All Tokens See Equally: Perception-Grounded Policy Optimization for Large Vision-Language Models

arXiv:2604.01840v2 Announce Type: replace Abstract: While Reinforcement Learning from Verifiable Rewards (RLVR) has advanced reasoning in Large Vision-Language Models (LVLMs), prevailing frameworks su

Phantasia: Context-Adaptive Backdoors in Vision Language Models

arXiv:2604.08395v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) have greatly enhanced the integration of visual perception and linguistic reasoning, driving rapid prog

researcharxiv-cs-cv

Rethinking Generalization in Reasoning SFT: A Conditional Analysis on Optimization, Data, and Model Capability

arXiv:2604.06628v1 Announce Type: new Abstract: A prevailing narrative in LLM post-training holds that supervised finetuning (SFT) memorizes while reinforcement learning (RL) generalizes. We revisit t

safetyarxiv-cs-ai

$S^3$: Stratified Scaling Search for Test-Time in Diffusion Language Models

arXiv:2604.06260v1 Announce Type: cross Abstract: Test-time scaling investigates whether a fixed diffusion language model (DLM) can generate better outputs when given more inference compute, without a

The Illusion of Superposition? A Principled Analysis of Latent Thinking in Language Models

arXiv:2604.06374v1 Announce Type: cross Abstract: Latent reasoning via continuous chain-of-thoughts (Latent CoT) has emerged as a promising alternative to discrete CoT reasoning. Operating in continuo

Applications

TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding

arXiv:2511.19693v3 Announce Type: replace-cross Abstract: Payment networks form the backbone of modern commerce, generating high volumes of transaction records from daily activities. Properly modeling

applicationsarxiv-cs-ai

Variational Feature Compression for Model-Specific Representations

model-releasesarxiv-cs-lg

arXiv:2604.06644v1 Announce Type: cross Abstract: As deep learning inference is increasingly deployed in shared and cloud-based settings, a growing concern is input repurposing, in which data submitte

Applications

Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment

arXiv:2604.08212v1 Announce Type: new Abstract: General-purpose vision-language models demonstrate strong performance in everyday domains but struggle with specialized technical fields requiring preci

applicationsarxiv-cs-cv

Vision-Language Navigation for Aerial Robots: Towards the Era of Large Language Models

model-releasesarxiv-cs-ro

arXiv:2604.07705v1 Announce Type: new Abstract: Aerial vision-and-language navigation (Aerial VLN) aims to enable unmanned aerial vehicles (UAVs) to interpret natural language instructions and autonom

When Numbers Speak: Aligning Textual Numerals and Visual Instances in Text-to-Video Diffusion Models

arXiv:2604.08546v1 Announce Type: new Abstract: Text-to-video diffusion models have enabled open-ended video synthesis, but often struggle with generating the correct number of objects specified in a

safetyarxiv-cs-cv

AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

arXiv:2608.12307v1 Announce Type: cross Abstract: Recent work on distillation transfers the capabilities of large models to smaller ones often by updating the latter's parameters, through teacher forc

13 Aug 2026

Quantization Damage Is Multiplicative, Not Additive

arXiv:2608.06564v1 Announce Type: cross Abstract: Quantization is how large language models are actually deployed, and below four bits it is known to hurt. What nobody can say is which of the model's

10 Aug 2026

Diagnosing Tool-Selection Reasoning in LLM Agents with Canary Tools

arXiv:2608.04719v1 Announce Type: new Abstract: Agent evaluations tell us that a model picked the wrong tool, but rarely why. We introduce canary tools: diagnostic probe tools planted in an agent's Mo

6 Aug 2026

SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials

arXiv:2509.21079v2 Announce Type: replace Abstract: Foundation models have shown remarkable capabilities in various domains, but their performance on complex, multimodal engineering problems remains l