Search: “models”

How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions

arXiv:2606.08051v1 Announce Type: new Abstract: Financial transaction processing requires extracting structured merchant information from noisy, abbreviated bank transaction strings at scale. Our curr

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IDDM: Identity-Decoupled Personalized Diffusion Models with a Tunable Privacy-Utility Trade-off

DGX agent

arXiv:2604.00903v2 Announce Type: replace Abstract: Personalized text-to-image diffusion models (e.g., DreamBooth, LoRA) enable users to synthesize high-fidelity avatars from a few reference photos fo

model-releasesarxiv-cs-cv

9 Jun 2026

PRISM: PRior-guided Imagination Sampling in world Models

arXiv:2606.07974v1 Announce Type: cross Abstract: A learned world model provides a powerful physical intuition for evaluating future states. But its effectiveness in continuous control also depends cr

When Do Local Score Models Extrapolate Across Size? A Diagnostic Theory and Benchmark

arXiv:2606.09705v1 Announce Type: new Abstract: Scientific generative modeling often requires size transfer, where models trained on small systems are evaluated on larger ones. While translation-invar

Where Instruction Hierarchy Breaks: Diagnosing and Repairing Failures in Reasoning Language Models

arXiv:2606.07808v1 Announce Type: new Abstract: Reasoning language models deployed in agentic workflows must follow an instruction hierarchy: when instructions from different sources conflict, the mod

Drifting Models for Surrogate Flow Modeling

arXiv:2606.07481v1 Announce Type: new Abstract: While Computational Fluid Dynamics (CFD) provides high-fidelity flow fields for optimizing indoor environments, its computational cost limits rapid expl

researcharxiv-cs-lg

8 Jun 2026

Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases

arXiv:2606.05112v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically del

4 Jun 2026

GENEB: Why Genomic Models Are Hard to Compare

arXiv:2606.04525v1 Announce Type: new Abstract: Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reportin

4 Jun 2026

Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use

arXiv:2603.03205v2 Announce Type: replace Abstract: Agentic language models operate in a fundamentally different safety regime than chat models: they must plan, call tools, and execute long-horizon ac

4 Jun 2026

From Answers to States: Verifiable Process-Level Evaluation of Chemical Reasoning in Large Language Models

arXiv:2606.03660v1 Announce Type: new Abstract: Large language models are increasingly used as chemistry assistants, yet most chemistry benchmarks still score only final answers. This masks a critical

3 Jun 2026

Greener Than Humans? Environmental Attitudes in Large Language Models

arXiv:2606.02741v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in sustainability-related decision support, reporting, and public communication, yet little systemati

3 Jun 2026

Geometry-Aware Implicit Memory for Video World Models

arXiv:2606.02436v1 Announce Type: new Abstract: Video world models aim to simulate controllable visual environments, but long-horizon rollouts depend on what the model remembers after observations lea

MBench: A Comprehensive Benchmark on Memory Capability for Video World Models

arXiv:2606.00793v1 Announce Type: new Abstract: Recent advancements in video-based world models have demonstrated an unprecedented ability to synthesize high-fidelity visual sequences. However, a fund

T1: Tool-integrated Verification for Test-time Compute Scaling in Small Language Models

arXiv:2504.04718v2 Announce Type: replace-cross Abstract: Recent studies have demonstrated that test-time compute scaling effectively improves the performance of small language models (sLMs). However,

Where to Look: Can Foundation Models Reach a Target Viewpoint Through Active Exploration?

arXiv:2606.01247v1 Announce Type: new Abstract: Humans can reproduce the viewpoint specified by a target image through active head and body motion, yet spatial intelligence in foundation models has la

Diversity Matters: Revisiting Test-Time Compute in Vision-Language Models

arXiv:2605.30713v1 Announce Type: cross Abstract: Test-time compute (TTC) strategies have emerged as a lightweight approach to boost reasoning in large language models (LLMs). However, their applicati

researcharxiv-cs-cv

1 Jun 2026

AtomWorld: A Benchmark for Evaluating Spatial Reasoning in Large Language Models on Crystalline Materials

arXiv:2510.04704v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promising potential in scientific research, enabling tasks ranging from knowledge retrieval to propert

Benchmarking Open-Source Safety Guard Models: A Comprehensive Evaluation

arXiv:2605.28830v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed in safety-critical applications, robust content moderation becomes essential. We present a c

Beyond Accuracy: Are Time Series Foundation Models Well-Calibrated?

arXiv:2510.16060v2 Announce Type: replace-cross Abstract: The recent development of foundation models for time series data has generated considerable interest in using such models across a variety of

researcharxiv-cs-ai

CosmicFish-HRM: Adaptive Reasoning via Hierarchical Recurrent Mechanisms in Compact Language Models

arXiv:2605.28919v1 Announce Type: cross Abstract: Large language models have achieved strong reasoning capabilities, though often at the cost of massive parameter counts and expensive inference. In th

DenseSteer: Steering Small Language Models towards Dense Math Reasoning

arXiv:2605.29247v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate strong chain-of-thought (CoT) reasoning abilities, while smaller models (<= 3B parameters) significantly underp

Why Far Looks Up: Probing Spatial Representation in Vision-Language Models

arXiv:2605.30161v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D und

Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data

arXiv:2605.27618v1 Announce Type: new Abstract: Despite the wide use of explainability techniques to attempt to understand the behavior of Artificial Intelligence (AI), the generated explanations may

Tutorials

Evaluation of AI Ethics Tools in Language Models: A Developers' Perspective Case Study

arXiv:2512.15791v2 Announce Type: replace-cross Abstract: In Artificial Intelligence (AI), language models have gained significant importance due to the widespread adoption of systems capable of simul

tutorialsarxiv-cs-ai

FedMPT: Federated Multi-label Prompt Tuning of Vision-Language Models

arXiv:2605.28347v1 Announce Type: new Abstract: Multi-Label Recognition (MLR) based on Vision-Language Models (VLMs) aims to leverage their pre-trained knowledge to better adapt complex recognition sc

Tutorials

Learning Correlated Reward Models: Statistical Barriers and Opportunities

arXiv:2510.15839v2 Announce Type: replace Abstract: Random Utility Models (RUMs) are a classical framework for modeling user preferences and play a key role in reward modeling for Reinforcement Learni

tutorialsarxiv-cs-lg

PetroBench: A Benchmark for Large Language Models in Petroleum Engineering

arXiv:2605.28032v1 Announce Type: new Abstract: Large Language Models are increasingly applied in the petroleum industry, highlighting the need for a domain-specific evaluation framework. This study d

SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding

arXiv:2601.21666v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) are a major focus of recent AI research. However, most prior work focuses on static image understanding, wh

When Context Flips, Safety Breaks: Diagnosing Brittle Safety in Aligned Language Models

arXiv:2605.27851v1 Announce Type: new Abstract: Safety benchmark scores provide incomplete evidence of deployment readiness: aligned language models often adhere to rigid rules even when a situational

When Interpretability Is Unequally Distributed: Fairness in Hybrid Interpretable Models

arXiv:2605.28626v1 Announce Type: new Abstract: Hybrid interpretable models combine a transparent component with a black-box model by assigning some examples to the former and deferring the rest to th

Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation

arXiv:2511.14993v3 Announce Type: replace-cross Abstract: This report introduces Kandinsky 5.0, a family of state-of-the-art foundation models for high-resolution image and 10-second video synthesis.

27 May 2026

Learning to Predict Future-Aligned Research Proposals with Language Models

arXiv:2603.27146v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to assist ideation in research, but evaluating the quality of LLM-generated research proposals re

27 May 2026

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation

arXiv:2507.16116v2 Announce Type: replace Abstract: The rapid advancement of video diffusion models has been hindered by fundamental limitations in temporal modeling, particularly the rigid synchroniz

researcharxiv-cs-cv

27 May 2026

How Well Do Models Follow Their Constitutions?

arXiv:2605.24229v1 Announce Type: new Abstract: Frontier AI developers now train models against long written behavioral specifications, such as Anthropic's constitution (Anthropic, 2025a) and OpenAI's

26 May 2026

Complete-muE: Optimal Hyperparameter Transfer and Scaling for MoE Models

arXiv:2605.23893v1 Announce Type: new Abstract: We propose Complete-muE, a framework which targets hyperparameter transfer across dense FFN and any Mixture-of-Experts (MoE) setups in transformer block

25 May 2026

Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models

arXiv:2605.21573v1 Announce Type: new Abstract: We introduce Lens, a 3.8B-parameter T2I model that achieves performance competitive with, and in several cases surpassing, state-of-the-art models with

22 May 2026

Safety

Reinforcing VLAs in Task-Agnostic World Models

arXiv:2605.12334v2 Announce Type: replace Abstract: Post-training Vision-Language-Action (VLA) models via reinforcement learning (RL) in learned world models has emerged as an effective strategy to ad

safetyarxiv-cs-ai

22 May 2026

Toxic Subword Pruning for Dialogue Response Generation on Large Language Models

arXiv:2410.04155v2 Announce Type: replace Abstract: How to defend large language models (LLMs) from generating toxic content is an important research area. Yet, most research focused on various model

21 May 2026

Eliminating Inductive Bias in Reward Models with Information-Theoretic Guidance

arXiv:2512.23461v2 Announce Type: replace-cross Abstract: Reward models (RMs) are essential in reinforcement learning from human feedback (RLHF) to align large language models (LLMs) with human values

20 May 2026

Flash PD-SSM: Memory-Optimized Structured Sparse State-Space Models

arXiv:2605.19150v1 Announce Type: cross Abstract: State-space models (SSMs) face a fundamental trade-off between efficiency and expressivity that is mainly dictated by the structure of the model's tra

researcharxiv-cs-ai

20 May 2026

Threats to Arabic Handwriting Recognition: Investigating Black-Box Adversarial Attacks on embedded ConvNet models

arXiv:2605.18058v1 Announce Type: new Abstract: Arabic handwriting recognition (AHR) has made significant progress with deep learning models. AHR research has largely focused on performance, with secu

19 May 2026

A Cross-Modal Prompt Injection Attack against Large Vision-Language Models with Image-Only Perturbation

arXiv:2605.16090v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have emerged as a powerful paradigm for multimodal intelligence, but their growing deployment also expands the at

Tutorials

A Unified View of Score-Based and Drifting Models

arXiv:2603.07514v3 Announce Type: replace-cross Abstract: Drifting models train one-step generators by optimizing a kernel-induced mean-shift discrepancy between the data and model distributions, with

tutorialsarxiv-cs-ai

Genome-Factory: A Library for Tuning, Deploying, and Interpreting Genomic Foundation Models

arXiv:2509.12266v2 Announce Type: replace-cross Abstract: We introduce Genome-Factory, the first integrated Python library for tuning, deploying, and interpreting genomic foundation models. Our core c

Quantization Undoes Alignment: Bias Emergence in Compressed LLMs Across Models and Precision Levels

arXiv:2605.15208v1 Announce Type: cross Abstract: Large Language Models are routinely compressed via post-training quantization to reduce inference costs and memory footprint for cloud and edge deploy

Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models

arXiv:2511.08565v3 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly operate in social contexts, motivating analysis of how they express and shift moral judgments. In th

15 May 2026

On the Cultural Anachronism and Temporal Reasoning in Vision Language Models

arXiv:2605.15071v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly applied to cultural heritage materials, from digital archives to educational platforms. This work ident

15 May 2026

Tokenizer Fertility and Zero-Shot Performance of Foundation Models on Ukrainian Legal Text: A Comparative Study

arXiv:2605.14890v1 Announce Type: new Abstract: Foundation models tokenize Ukrainian legal text with vastly different efficiency, yet no systematic comparison exists for this domain. We benchmark seve