Search: “models”

DiTailed: Ensuring Visual Object Consistency in Text-Image-to-Image Flow Matching Models

arXiv:2607.12539v1 Announce Type: new Abstract: Despite remarkable progress in text-guided image editing, generative models frequently fail to preserve visual object consistency, defined as the preser

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Evaluating Health Misinformation in Low-Resource Languages: Integrating Small Language Models with a Culturally-Sensitive Responsible NLP Framework (Bangla as a Case Study)

DGX agent

arXiv:2607.12336v1 Announce Type: cross Abstract: Artificial Intelligence (AI) technologies, while serving as a foundational enabler for modern social media and digital health services, exert a bivale

model-releasesarxiv-cs-ai

15 Jul 2026

Safety

Growing a Tail: Increasing Output Diversity in Large Language Models

arXiv:2411.02989v2 Announce Type: replace Abstract: How diverse are the outputs of large language models when diversity is desired? We examine the diversity of responses of several language models to

safetyarxiv-cs-cl

The Computational Basis of Confidence in Large Language Models

arXiv:2607.12447v1 Announce Type: cross Abstract: Reliable confidence -- the probability that a model's own answer is correct -- is essential for the trustworthy deployment of language models. Existin

researcharxiv-cs-ai

Agents

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

agentsarxiv-cs-ai

Local Ai

An exact information theory of generalization phase transitions in Bayesian diffusion models

arXiv:2607.08041v1 Announce Type: new Abstract: How diffusion models circumvent the curse of dimensionality to learn complex distributions over high dimensional spaces from a finite training set, inst

local-aiarxiv-cs-lg

10 Jul 2026

Beyond wheelchairs and blindfolds: Investigating disability stereotypes in T2I models with INCLUDE-BENCH

arXiv:2607.08515v1 Announce Type: new Abstract: Text-to-image (T2I) models have been shown to exhibit social biases. Prior work has mainly focused on gender, skin tone, and cultural representation wit

10 Jul 2026

Diffusion Models in Simulation-Based Inference: A Tutorial Review

model-releasesarxiv-cs-lg

arXiv:2512.20685v3 Announce Type: replace-cross Abstract: Diffusion models have recently emerged as powerful learners for simulation-based inference (SBI), enabling fast and accurate estimation of lat

9 Jul 2026

FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models

arXiv:2607.05711v1 Announce Type: cross Abstract: Diffusion models have become a dominant paradigm for high-quality generative modeling, while post-training is essential for adapting them to diverse d

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction

arXiv:2607.05568v1 Announce Type: cross Abstract: Representing 3D shapes as compact sets of geometric primitives is fundamental to robotics, simulation, and scene understanding. Generative image model

Performance Optimization and Comparative Analysis of Generative AI Models on Advanced Accelerators

arXiv:2607.05400v1 Announce Type: cross Abstract: Generative AI models, such as Large Language Models (LLMs) and diffusion models, have demonstrated impressive performance across a wide range of tasks

researcharxiv-cs-lg

The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer

arXiv:2502.15631v2 Announce Type: replace-cross Abstract: Large language models have demonstrated remarkable progress in mathematical reasoning, leveraging chain-of-thought and reinforcement learning.

Brand-as-Memory: Vision-Language Models Encode Causal, Mechanistically Localizable Credibility Priors for News Sources

arXiv:2607.03365v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly read news and web content as images, where the publisher's identity is visually present. We show that VLMs

Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models

arXiv:2607.02575v1 Announce Type: cross Abstract: Vision-language models can perform new tasks without parameter updates through in-context learning (ICL), whose core mechanism is utilizing the suppor

EvoXplain: When Machine Learning Models Agree on Predictions but Disagree on Why -- Measuring Mechanistic Multiplicity Across Training Runs

arXiv:2512.22240v5 Announce Type: replace-cross Abstract: Machine learning models are primarily judged by predictive performance, especially in applied genomics, where explanations are read as biologi

researcharxiv-cs-ai

Multiplayer Interactive World Models with Representation Autoencoders

arXiv:2607.05352v1 Announce Type: cross Abstract: We introduce the first multiplayer world model for highly dynamic environments governed by complex physical interactions. Whereas single-player world

No Reliable Evidence of Self-Reported Sentience in Small Large Language Models

arXiv:2601.15334v2 Announce Type: replace-cross Abstract: Whether language models possess sentience has no empirical answer. But whether they believe themselves to be sentient can, in principle, be te

Local Ai

Trust-Region Noise Search for Black-Box Alignment of Diffusion and Flow Models

arXiv:2603.14504v2 Announce Type: replace-cross Abstract: Optimizing the noise samples of diffusion and flow models is an increasingly popular approach to align these models to target rewards at infer

local-aiarxiv-cs-ai

Comparing Large Language Models on Scrum Certification-Style Questions: Accuracy, Stability, and Error Patterns

arXiv:2607.00048v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in exam- and certification-style question answering tasks, where their ability to retrieve, interpr

2 Jul 2026

Steal the Patch Size: Adversarially Manipulate Vision-Language Models

arXiv:2607.00174v1 Announce Type: new Abstract: We present a black-box model-stealing attack that recovers private vision-tokenizer configurations of deployed vision-language models (VLMs), including

2 Jul 2026

Utilizing Earth Foundation Models to Enhance the Simulation Performance of Hydrological Models with AlphaEarth Embeddings

arXiv:2601.01558v2 Announce Type: replace-cross Abstract: Predicting river flow in places without streamflow records is challenging because basins respond differently to climate, terrain, vegetation,

researcharxiv-cs-ai

2 Jul 2026

Safety

How Should World Models Be Evaluated for Embodied Decision-Making? A Decision-Making-Centric Position

arXiv:2606.15032v2 Announce Type: replace Abstract: World models have become a central abstraction in modern AI. The term now refers to several different objects: action-conditioned environment models

safetyarxiv-cs-lg

On Test-Time Scaling for Vision-Language Models

arXiv:2606.28864v1 Announce Type: new Abstract: Test-time scaling is a paradigm where large models use additional compute at inference to achieve better performance, without changing model weights. Wh

researcharxiv-cs-cv

Representational Depth of Evaluation Awareness Shifts With Scale in Open-Weight Language Models

arXiv:2606.29196v1 Announce Type: cross Abstract: Do language models know when they are being tested? This question matters for AI safety: a model that recognises an evaluation context could alter its

SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models

arXiv:2606.29815v1 Announce Type: new Abstract: Evaluating code large language models (Code LLMs) requires reliable detection of data leakage, where benchmark performance is artificially inflated by e

The Digital Afterlife of Empires: Four Language Models Converge on the Same Imperial Cartography of Writing

arXiv:2606.28325v1 Announce Type: cross Abstract: Large language models process the world's writing systems with radical inequality. We constructed the Digital Script Representation Index (DSRI), a se

When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models

arXiv:2602.10179v2 Announce Type: replace-cross Abstract: Recent advances in large image editing models have shifted the paradigm from text-driven instructions to vision-prompt editing, where user int

29 Jun 2026

Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models

arXiv:2606.26566v1 Announce Type: cross Abstract: Adversarial evaluation of AI systems has matured along four largely disconnected tracks: diffusion-based attacks on text and large language models (LL

Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models

arXiv:2606.14122v2 Announce Type: replace Abstract: Byte-level tokenization enables language models to handle any Unicode input, but models can generate invalid UTF-8 sequences when encountering rare

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models

arXiv:2606.26287v1 Announce Type: new Abstract: With the increase in model parameters and training data, the instruction following and generalization capabilities of Large VisionLanguage Models (LVLMs

Hallucination in World Models is Predictable and Preventable

arXiv:2606.27326v1 Announce Type: cross Abstract: Modern generative world models render increasingly realistic action-controllable futures, yet they frequently hallucinate: rollouts remain visually fl

HarmVideoBench: Benchmarking Harmful Video Understanding in Large Multimodal Models

arXiv:2606.27187v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have recently shown immense potential in automated content moderation, sparking growing interest in developing ha

The Inattentional Gap: Task-Conditioned Language and Vision Models Omit the Safety-Critical Signals They Can Otherwise Report

arXiv:2606.26529v1 Announce Type: cross Abstract: AI safety is evaluated by how reliably a model detects the hazards it is told to find, yet accidents often arise from the hazard no one specified. We

A Red Teaming Framework for Large Language Models: A Case Study on Faithfulness Evaluation

arXiv:2606.25476v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable performance across natural language processing tasks, yet their deployment in high-stakes appl

25 Jun 2026

Internal Data Repetition Destroys Language Models

model-releasesarxiv-cs-lg

arXiv:2606.24998v1 Announce Type: new Abstract: Language models are running out of high-quality training data, and even aggressively deduplicated corpora retain some amount of repetition. Earlier cont

25 Jun 2026

Small edits, large models: How Wikipedia advocacy shapes LLM values

arXiv:2606.24890v1 Announce Type: new Abstract: Can a small group of volunteers shape how AI systems discuss animal welfare, just by editing Wikipedia? We show that they can. Wikipedia appears in near

25 Jun 2026

Local Ai

CrossPool: Efficient Multi-LLM Serving for Cold MoE Models through KV-Cache and Weight Disaggregation

arXiv:2606.24506v1 Announce Type: cross Abstract: Emerging LLM services increasingly host many sparse MoE models, yet most models receive sparse requests and remain cold. This creates a GPU memory pro

local-aiarxiv-cs-ai

24 Jun 2026

Grounded Chess Reasoning in Language Models via Master Distillation

arXiv:2603.20510v2 Announce Type: replace Abstract: Language models often lack grounded reasoning capabilities in specialized domains where training data is scarce but bespoke systems excel. We introd

24 Jun 2026

OpenThoughts-Agent: Data Recipes for Agentic Models

arXiv:2606.24855v1 Announce Type: new Abstract: Agentic language models dramatically expand the applications of AI yet little is publicly known about how to curate training data for broadly capable ag

24 Jun 2026

Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning

arXiv:2606.21775v1 Announce Type: new Abstract: Recently, world models have emerged as a promising paradigm for building intelligent agents by learning predictive models that estimate future environme

researcharxiv-cs-lg

Discretizing Reward Models

arXiv:2606.21795v1 Announce Type: new Abstract: Despite their widespread use, the role of reward models in shaping reinforcement learning is poorly understood. Reward models offer a tempting promise:

researcharxiv-cs-lg

Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models using Reinforcement Learning from Ranking Feedback

arXiv:2510.02561v2 Announce Type: replace Abstract: Recent advances in large video-language models (VLMs) rely on extensive fine-tuning techniques that strengthen alignment between textual and visual

Who Owns the AI Recommendation? A Multi-Industry Empirical Map of Brand Category Ownership Across Large Language Models

model-releasesarxiv-cs-lg

arXiv:2606.23057v1 Announce Type: cross Abstract: Large language models now mediate how buyers discover products and services, making the competitive structure of AI-generated recommendations a strate

ICA Lens: Interpreting Language Models Without Training Another Dictionary

arXiv:2606.11722v1 Announce Type: cross Abstract: Finding interpretable directions in language-model representations is critical for understanding and controlling model behavior. Sparse autoencoders (

11 Jun 2026

Applications

BiWM: Advancing Open-Source Interactive Video World Models with Bidirectional Autoregression

arXiv:2606.10135v1 Announce Type: cross Abstract: Transitioning bidirectional video diffusion models into an autoregressive paradigm improves the interactivity of video world models, but existing caus

applicationsarxiv-cs-ai

10 Jun 2026

Calibration of Structured Ignorance Certificates for Diagnosing Unknown Unknowns in Reasoning Models

arXiv:2606.08571v1 Announce Type: cross Abstract: Large language models frequently fail in a characteristic way: rather than acknowledging ignorance, they produce fluent but incorrect answers to quest

9 Jun 2026

DisCo: World Models with Discrete Camera Motion Control

arXiv:2606.07967v1 Announce Type: new Abstract: Controllable video world models target interactive world exploration, where models must faithfully execute explicit action commands while preserving vis

9 Jun 2026

Tutorials

From inverse problems to neural operators: prediction, mechanism, and generalization of data-driven models