Search: “models”

Mamba Policy: Towards Efficient 3D Diffusion Policy with Hybrid Selective State Models

arXiv:2409.07163v3 Announce Type: replace-cross Abstract: Diffusion models have been widely employed in the field of 3D manipulation due to their efficient capability to learn distributions, allowing

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Hardware

MiniWorld: Democratizing the Training of Video World Models from Scratch

DGX agent

arXiv:2608.01127v1 Announce Type: new Abstract: Video world models predict future observations conditioned on historical observations and control signals, enabling long-horizon generation through auto

hardwarearxiv-cs-cv

4 Aug 2026

Not the Dimension, the Norm: What Matters in Gradient-Free Weight Perturbation of Language Models

arXiv:2608.01624v1 Announce Type: new Abstract: Adapting a language model to a task no longer requires training all of its weights, and a line of parameter-efficient methods has driven the trainable c

Semantic Alignment of AI Models: Concept Collapse, Checkpoint Dynamics, and Cross-Lingual Transfer

arXiv:2608.01585v1 Announce Type: new Abstract: Language model benchmarking is a difficult task. Outcome reasoning alone does not test the model's conceptualization of language and popular open-source

safetyarxiv-cs-cl

SPARC-Rad: A Multimodal Benchmark Dataset and Evaluation Pipeline for Spatial and Anatomical Reasoning in Radiology Vision-Language Models

arXiv:2608.00100v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly being evaluated for medical imaging, but many available benchmarks emphasize disease classification, repo

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives

arXiv:2607.29064v1 Announce Type: cross Abstract: Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclea

3 Aug 2026

DiffAttack: Evasion Attacks Against Face Recognition via Latent Diffusion Models

arXiv:2607.28936v1 Announce Type: cross Abstract: Facial biometric identification relies on the distinctiveness of user attributes within a high-dimensional embedding space. However, the decision boun

3 Aug 2026

Fisher Information, Training and Bias in Fourier Regression Models

arXiv:2510.06945v2 Announce Type: replace Abstract: Motivated by the growing interest in quantum machine learning, in particular quantum neural networks (QNNs), we study how recently introduced evalua

safetyarxiv-cs-lg

3 Aug 2026

Ask don't tell: Reducing sycophancy in large language models

arXiv:2602.23971v4 Announce Type: replace-cross Abstract: Sycophancy, the tendency of large language models to favour user-affirming responses over critical engagement, has been identified as an align

safetyarxiv-cs-ai

KAISEN: Reproducible Subgroup Fairness Auditing for Clinical Risk Models

model-releasesarxiv-cs-lg

arXiv:2607.28608v1 Announce Type: new Abstract: Clinical risk models routinely achieve strong aggregate performance while producing materially different error rates across patient subgroups. Audit pip

MedHallTune: An Instruction-Tuning Benchmark for Mitigating Medical Hallucination in Vision-Language Models

arXiv:2502.20780v2 Announce Type: replace-cross Abstract: The increasing use of vision-language models (VLMs) in healthcare applications presents great challenges related to hallucinations, in which t

MRD: Using Physically Based Differentiable Rendering to Probe Vision Models for 3D Scene Understanding

arXiv:2512.12307v5 Announce Type: replace Abstract: While deep learning methods have achieved impressive success in many vision benchmarks, it remains difficult to understand and explain the represent

researcharxiv-cs-cv

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models

arXiv:2607.28609v1 Announce Type: cross Abstract: Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Veri

QuantWAMs: Calibrating at the Right Granularity for World Action Models

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

researcharxiv-cs-lg

Scaling Vision-Language Models Is Not Enough to Mitigate Bias

arXiv:2607.28211v1 Announce Type: new Abstract: Vision-Language Models (VLMs) such as CLIP are now foundational to multimodal systems, yet their robustness to spurious correlations remains poorly unde

The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models

arXiv:2602.08159v2 Announce Type: replace-cross Abstract: When a language model asserts that 'the capital of Australia is Sydney,' does it know this is wrong? Models assert misconceptions with the sam

safetyarxiv-cs-cl

Foundation Models for Face Presentation Attack Detection: A Unified Linear-Probing Benchmark

model-releasesarxiv-cs-lg

arXiv:2607.26993v1 Announce Type: new Abstract: Face presentation attack detection (PAD) remains challenging under cross-dataset evaluation, where domain shift degrades models trained on a single data

Learning Implicit Causal World Models from Multi-Agent Demonstrations

arXiv:2607.26336v1 Announce Type: new Abstract: In model-based reinforcement learning, world models exist as internal simulators, but their training often conflates statistical correlations with causa

safetyarxiv-cs-lg

Probing the Origins of Reasoning Performance: Representational Quality for Mathematical Problem-Solving in RL vs. SFT Fine-Tuned Models

arXiv:2607.26119v1 Announce Type: cross Abstract: Large reasoning models trained via reinforcement learning (RL) have been increasingly shown to outperform their supervised fine-tuned (SFT) counterpar

safetyarxiv-cs-cl

VideoNorms: Benchmarking Cultural Awareness of Video Language Models

arXiv:2510.08543v2 Announce Type: replace-cross Abstract: As Video Large Language Models (VideoLLMs) are deployed globally, it is important to assess their ability to reason across cultural contexts.

researcharxiv-cs-cl

Walk through Paintings: Egocentric World Models from Internet Priors

arXiv:2601.15284v2 Announce Type: replace Abstract: What if a video generation model could not only imagine a plausible future, but the correct one -- accurately reflecting how the world changes with

researcharxiv-cs-cv

Building Large-Scale English-Romanian Literary Translation Resources with Open Models

arXiv:2509.07829v4 Announce Type: replace-cross Abstract: Literary translation has recently gained attention as a distinct and complex task in machine translation research, yet translation by small op

Local Ai

I2VShield: An Efficient Proactive Defense Framework against DiT-based Image-to-Video Models

arXiv:2607.25522v1 Announce Type: cross Abstract: The rapid advancement of video generation models has led to the increasing misuse of image-to-video (I2V) models. Although substantial progress has be

local-aiarxiv-cs-ai

Influence of Prompt Engineering on Small Language Models for Guarded Query Routing

arXiv:2607.24801v1 Announce Type: cross Abstract: We study the problem of guarded query routing, where we assume that a user query first meets a router that either determines the ideal endpoint for in

Measuring and Improving Behavioral Consistency in Large Language Models through Fact-Heuristic-Emotion State Enforcement

arXiv:2607.24765v1 Announce Type: cross Abstract: Large language models (LLMs) can give different answers to the same decision problem across runs, and reverse a decision when their own prior answer r

Local Ai

TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models

arXiv:2507.10643v4 Announce Type: replace-cross Abstract: Post-hoc model-agnostic local attribution (LA) methods have been widely adopted to explain opaque AI models by quantifying feature-wise contri

local-aiarxiv-cs-ai

AgentOmnia: Scaling Agentic Models for Full-Scenario Applications

arXiv:2607.23124v1 Announce Type: new Abstract: Large language model agents have advanced rapidly, yet progress remains fragmented across domains, capabilities, task difficulty, and interaction settin

Algorithmic Blindness in Large Language Models: A Calibration Study of Performance Prediction

arXiv:2602.21947v5 Announce Type: replace Abstract: Large language models (LLMs) demonstrate remarkable breadth of knowledge, yet their ability to reason about computational processes remains poorly u

Agents

AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models

arXiv:2603.28963v2 Announce Type: replace-cross Abstract: Simulation with realistic traffic agents is essential for validating autonomous driving systems. Existing data-driven simulators learn agent b

agentsarxiv-cs-ai

Extracting Algorithms in Pre-trained LLMs: A Case on Hidden Markov Models

arXiv:2607.22646v1 Announce Type: new Abstract: Large language models (LLMs) display a striking ability to predict next observations from Hidden Markov Models (HMMs) via in-context learning (ICL), but

Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach

arXiv:2607.24259v1 Announce Type: new Abstract: Recent work has explored the use of Large Language Models (LLMs) to automate simulation model building, typically by generating executable code directly

GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models

arXiv:2607.23913v1 Announce Type: new Abstract: Modern vision-language models (VLMs) increasingly rely on dynamic or high-resolution visual encoding, producing thousands of visual tokens that substant

INS-ActBench: A Comprehensive Benchmark for Assessing Professional Actuarial Capability of Large Language Models

arXiv:2607.24273v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential in financial reasoning, but existing benchmarks often evaluate domain knowledge, numerical reas

Reconstructing Item Characteristic Curves using Fine-Tuned Large Language Models

arXiv:2601.02580v2 Announce Type: replace-cross Abstract: Traditional methods for determining assessment item parameters, such as difficulty and discrimination, rely heavily on expensive field testing

Who Gets Named: Citation Type Predicts Individual Naming by Grounded Language Models, and a Roster Instrument Captures 0.5% of It

arXiv:2607.23893v1 Announce Type: cross Abstract: Prior work on AI brand visibility measures the firm: does a model recommend a company, and does that track its reputation. This study asks the questio

Analysing Self-Harm Representations in Language Models: a Cross-Architecture Study

arXiv:2607.21988v1 Announce Type: new Abstract: Self-harm content is particularly challenging to detect using NLP techniques, and is also a high-stakes task which requires the highest accuracy to enab

27 Jul 2026

Autoregressive EHR Foundation Models with Multimodal Inputs

arXiv:2607.22264v1 Announce Type: new Abstract: Autoregressive foundation models trained on tokenized electronic health records (EHRs) can support zero-shot clinical prediction, yet most operate on st

safetyarxiv-cs-lg

27 Jul 2026

Correlation-Aware and Gaussianity-Preserving Robust Latent Angular Watermarking for Diffusion Models

arXiv:2607.22386v1 Announce Type: new Abstract: Latent domain watermarking for diffusion models embeds watermarks directly into the latent prior, enjoying non-intrusiveness to model parameters and sea

researcharxiv-cs-cv

27 Jul 2026

An LLM-Driven Workflow for Automated Process Control Strategy Generation and Tuning from Dynamic Process Models

arXiv:2607.21292v1 Announce Type: new Abstract: We present a structured large-language-model-driven workflow for automated multi-variable control design from dynamic process models. The workflow decom

Expectation Alignment of Language Models for Real-World User Expectations

arXiv:2607.20485v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated remarkable performance on standard benchmarks, yet it remains largely unexplored whether they truly meet

HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models

arXiv:2607.21105v1 Announce Type: new Abstract: Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucin

Incomplete Prompt Jailbreaks in Large Language Models

arXiv:2607.20473v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly released as open-weight models with safeguards against harmful requests. Nevertheless, sentence completion

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models

arXiv:2607.19618v1 Announce Type: cross Abstract: Genomic language models achieve strong performance across regulatory-genomics tasks, yet what these models internally represent remains opaque, and th

Good Practice Guide for quantifying uncertainties for machine learning models applied to photoplethysmography signals

model-releasesarxiv-cs-lg

arXiv:2607.19999v1 Announce Type: new Abstract: This Good Practice Guide presents work done in the QUMPHY project (Uncertainty quantification for machine learning models applied to photoplethysmograph

KineBench: Benchmarking Embodied World Models via IDM-Free Kinematic Grounding

model-releasesarxiv-cs-ro

arXiv:2607.19876v1 Announce Type: new Abstract: Evaluating the physical consistency of embodied world models(EWMs) is a critical open challenge. While closed-loop evaluation via simulator rollouts off

When Visual Evidence is Ambiguous: Pareidolia as a Diagnostic Probe for Vision Models

arXiv:2603.03989v3 Announce Type: replace-cross Abstract: When visual evidence is ambiguous, vision models must decide how to interpret face-like patterns. Face pareidolia, the perception of faces in

Xiaomi-Robotics-1: Scaling Vision-Language-Action Models with over 100K Hours of Real-World Trajectories

model-releasesarxiv-cs-ro

arXiv:2607.15330v2 Announce Type: replace Abstract: We present Xiaomi-Robotics-1, a foundational vision-language-action (VLA) model capable of (1) following diverse language instructions to perform a

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation

arXiv:2603.00546v2 Announce Type: replace Abstract: Using Multimodal Large Language Models (MLLMs) as judges to achieve precise and consistent evaluations has gradually become an emerging paradigm acr