Search: “models”

The Efficiency Gap in Byte Modeling

arXiv:2605.12928v1 Announce Type: new Abstract: Modern language models have historically relied on two dominant design choices: subword tokenization and autoregressive (AR) ordering. These design deci

14 May 2026

AIA: Rethinking Architecture Decoupling Strategy In Unified Multimodal Model

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arXiv:2511.22663v5 Announce Type: replace Abstract: Unified multimodal models for image generation and understanding represent a significant step toward AGI and have attracted widespread attention fro

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13 May 2026

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training

arXiv:2605.12483v1 Announce Type: new Abstract: In settings where labeled verifiable training data is the binding constraint, each checked example should be allocated carefully. The standard practice

Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation

arXiv:2605.12034v1 Announce Type: cross Abstract: Omni-modal language models are intended to jointly understand audio, visual inputs, and language, but benchmark gains can be inflated when visual evid

Local Ai

CaC: Advancing Video Reward Models via Hierarchical Spatiotemporal Concentrating

arXiv:2605.11723v1 Announce Type: new Abstract: In this paper, we propose Concentrate and Concentrate (CaC), a coarse-to-fine anomaly reward model based on Vision-Language Models. During inference, it

local-aiarxiv-cs-cv

DarkQA: Benchmarking Vision-Language Models on Visual-Primitive Question Answering in Low-Light Indoor Scenes

arXiv:2512.24985v4 Announce Type: replace Abstract: Vision Language Models (VLMs) are increasingly adopted as central reasoning modules for embodied agents. Existing benchmarks evaluate their capabili

DriftXpress: Faster Drifting Models via Projected RKHS Fields

arXiv:2605.12183v1 Announce Type: new Abstract: Drifting Models have emerged as a new paradigm for one-step generative modeling, achieving strong image quality without iterative inference. The premise

GeneZip: Region-Aware Compression for Long Context DNA Modeling

arXiv:2602.17739v3 Announce Type: replace-cross Abstract: Long-context DNA models are limited by token-mixing cost and by how compression allocates representational budget across the genome. Existing

Language Modeling with Hyperspherical Flows

arXiv:2605.11125v1 Announce Type: new Abstract: Discrete Diffusion Language Models progressed rapidly as an alternative to autoregressive (AR) models, motivated by their parallel generation abilities.

Applications

OmniThoughtVis: A Scalable Distillation Pipeline for Deployable Multimodal Reasoning Models

arXiv:2605.11629v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown strong chain-of-thought (CoT) reasoning ability on vision-language tasks, but their direct de

applicationsarxiv-cs-cl

Overcoming Dynamics-Blindness: Training-Free Pace-and-Path Correction for VLA Models

arXiv:2605.11459v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models achieve remarkable flexibility and generalization beyond classical control paradigms. However, most prevailing VLA

Parameter-Efficient Adaptation of Pre-Trained Vision Foundation Models for Active and Passive Seismic Data Denoising

arXiv:2605.10953v1 Announce Type: cross Abstract: The demand for high-resolution subsurface imaging and continuous Earth monitoring has driven rapid growth in active and passive seismic data from dens

ReasonEdit: Editing Vision-Language Models using Human Reasoning

arXiv:2602.02408v4 Announce Type: replace Abstract: Model editing aims to correct errors in large, pretrained models without altering unrelated behaviors. While some recent works have edited vision-la

researcharxiv-cs-cv

Rethinking external validation for the target population: Capturing patient-level similarity with a generative model

arXiv:2605.11284v1 Announce Type: cross Abstract: Background: External validation is essential for assessing the transportability of predictive models. However, its interpretation is often confounded

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STRUM: A Spectral Transcription and Rhythm Understanding Model for End-to-End Generation of Playable Rhythm-Game Charts

arXiv:2605.12135v1 Announce Type: cross Abstract: We present STRUM (Spectral Transcription and Rhythm Understanding Model), an audio-to-chart pipeline that converts raw recordings into playable Clone

TCP-SSM: Efficient Vision State Space Models with Token-Conditioned Poles

arXiv:2605.11563v1 Announce Type: new Abstract: State Space Models (SSMs) have emerged as a compelling alternative to attention models for long-range vision tasks, offering input-dependent recurrence

researcharxiv-cs-cv

Alice v1: Distillation-Enhanced Video Generation Surpassing Closed-Source Models

arXiv:2605.08115v1 Announce Type: cross Abstract: Wepresent Alice v1, a 14-billion parameter open-source video generation model that achieves state-of-the-art quality through consistency distillation

Architecture, Not Scale: Circuit Localization in Large Language Models

arXiv:2605.08853v1 Announce Type: new Abstract: Mechanistic interpretability assumes that circuit analysis becomes harder as models scale. We challenge this assumption by showing that the attention ar

Beyond Language: Format-Agnostic Reasoning Subspaces in Large Language Models

arXiv:2605.09496v1 Announce Type: new Abstract: Large language models represent the same reasoning in vastly different surface forms -- English prose, Python code, mathematical notation -- yet whether

Beyond Local Edits: Embedding-Virtualized Knowledge for Broader Evaluation and Preservation of Model Editing

arXiv:2602.01977v2 Announce Type: replace Abstract: Knowledge editing methods for large language models are commonly evaluated using predefined benchmarks that assess edited facts together with a limi

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models

arXiv:2605.08404v1 Announce Type: cross Abstract: This work investigates the use of large language models (LLMs) for tasks in smart cities. The core idea is to leverage remote sensing imagery to chara

DeepSight: Long-Horizon World Modeling via Latent States Prediction for End-to-End Autonomous Driving

arXiv:2605.10564v1 Announce Type: new Abstract: End-to-end autonomous driving systems are increasingly integrating Vision-Language Model (VLM) architectures, incorporating text reasoning or visual rea

Local Ai

DUALFloodGNN: Physics-informed Graph Neural Network for Operational Flood Modeling

arXiv:2512.23964v2 Announce Type: replace-cross Abstract: Flood models inform strategic disaster management by simulating the spatiotemporal hydrodynamics of flooding. While physics-based numerical fl

local-aiarxiv-cs-ai

EnergyLens: Interpretable Closed-Form Energy Models for Multimodal LLM Inference Serving

arXiv:2605.10556v1 Announce Type: new Abstract: As large language models span dense, mixture-of-experts, and state-space architectures and are deployed on heterogeneous accelerators under increasingly

Equilibrium Residuals Expose Three Regimes of Matrix-Game Strategic Reasoning in Language Models

arXiv:2605.10410v1 Announce Type: new Abstract: Large language models can score well on named game-theory benchmarks while failing on the same strategic computation once semantic cues are removed. We

Local Ai

Event Fields: Learning Latent Event Structure for Waveform Foundation Models

arXiv:2605.08685v1 Announce Type: cross Abstract: We propose a new class of waveform foundation models that departs from conventional sequence based representations by modeling physiological time seri

local-aiarxiv-cs-ai

Holmes: A Benchmark to Assess the Linguistic Competence of Language Models

arXiv:2404.18923v5 Announce Type: replace Abstract: We introduce Holmes, a new benchmark designed to assess language models (LMs) linguistic competence - their unconscious understanding of linguistic

HoReN: Normalized Hopfield Retrieval for Large-Scale Sequential Model Editing

arXiv:2605.08143v1 Announce Type: cross Abstract: Large language models encode vast factual knowledge that inevitably becomes outdated or incorrect after deployment, yet retraining is costly prohibiti

How Mobile World Model Guides GUI Agents?

arXiv:2605.10347v1 Announce Type: new Abstract: Recent advances in vision-language models have enabled mobile GUI agents to perceive visual interfaces and execute user instructions, but reliable predi

researcharxiv-cs-ai

HyperTransport: Amortized Conditioning of T2I Generative Models

arXiv:2605.08254v1 Announce Type: cross Abstract: As foundation models grow in capability, the ability to efficiently and reliably control their behavior becomes critical. Fine-tuning these models can

researcharxiv-cs-ai

Improving Generalization by Permutation Routing Across Model Copies

arXiv:2605.09256v1 Announce Type: cross Abstract: We introduce a use of the (M)-cover (or (M)-layer) transform for machine learning. The method replicates a model (M) times, but instead of coupling th

LEAD: Length-Efficient Adaptive and Dynamic Reasoning for Large Language Models

arXiv:2605.09806v1 Announce Type: cross Abstract: Large reasoning models, such as OpenAI o1 and DeepSeek-R1, tend to become increasingly verbose as their reasoning capabilities improve. These inflated

LLM Jaggedness Unlocks Scientific Creativity

arXiv:2605.10574v1 Announce Type: new Abstract: As artificial intelligence advances, models are not improving uniformly. Instead, progress unfolds in a jagged fashion, with capabilities growing uneven

M2A: Synergizing Mathematical and Agentic Reasoning in Large Language Models

arXiv:2605.09879v1 Announce Type: new Abstract: While reasoning has become a central capability of large language models (LLMs), the reasoning patterns required for different scenarios are often misal

Applications

Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning

arXiv:2605.09771v1 Announce Type: new Abstract: Despite the central role of sensor-derived measurements such as imaging traits and plasma biomarkers in biomedical research and clinical practice, exist

applicationsarxiv-cs-ai

PoDAR: Power-Disentangled Audio Representation for Generative Modeling

arXiv:2605.10084v1 Announce Type: cross Abstract: The performance of audio latent diffusion models is primarily governed by generator expressivity and the modelability of the underlying latent space.

researcharxiv-cs-ai

Political Plasticity: An Analysis of Ideological Adaptability in Large Language Models

arXiv:2605.08415v1 Announce Type: new Abstract: Since the advent of Large Language Models (LLMs), a significant area of research has focused on their intrinsic biases, particularly in political discou

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PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models

arXiv:2605.08800v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) may memorize sensitive cross-modal information during pretraining. However, existing MLLM unlearning benchmar

QM-ToT: A Medical Tree of Thoughts Reasoning Framework for Quantized Model

arXiv:2504.12334v2 Announce Type: replace Abstract: Large language models (LLMs) face significant challenges in specialized biomedical tasks due to the inherent complexity of medical reasoning and the

Quantitative Clustering in Mean-Field Transformer Models

arXiv:2504.14697v3 Announce Type: replace Abstract: The evolution of tokens through deep transformer models can be modeled as an interacting particle system that has been shown to exhibit an asymptoti

Revitalizing the Beginning: Avoiding Storage Dependency for Model Merging in Continual Learning

arXiv:2605.08311v1 Announce Type: cross Abstract: Model merging provides a compelling paradigm for integrating specialized expertise into a unified multi-task model, a goal that aligns naturally with

safetyarxiv-cs-cv

SalesSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators

arXiv:2605.08334v1 Announce Type: new Abstract: We present SalesSim, a framework and testbed for evaluating the ability of Multimodal Large Language Models (MLLMs) to simulate realistic, persona-drive

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Spherical Boltzmann machines: a solvable theory of learning and generation in energy-based models

arXiv:2605.09031v1 Announce Type: new Abstract: Energy-based models (EBMs) are flexible generative architectures inspired by statistical physics, but their learning and generative properties remain po

The Echo Amplifies the Knowledge: Somatic Marker Analogues in Language Models via Emotion Vector Re-Injection

arXiv:2605.08611v1 Announce Type: new Abstract: Current language model memory systems store what happened but not how it felt. This distinction -- between semantic memory (knowing about a past event)

The World is Not Mono: Enabling Spatial Understanding in Large Audio-Language Models

arXiv:2601.02954v3 Announce Type: replace-cross Abstract: Large audio-language models have made rapid progress in recognizing what is present in an audio clip, but spatial audio-language understanding

TOC-Bench: A Temporal Object Consistency Benchmark for Video Large Language Models

arXiv:2605.09904v1 Announce Type: new Abstract: Video large language models (Video-LLMs) have achieved remarkable progress in general video understanding, yet their ability to maintain temporal object

Tracing Moral Foundations in Large Language Models

arXiv:2601.05437v2 Announce Type: replace-cross Abstract: Large language models often produce human-like moral judgments, but it is unclear whether this reflects an internal conceptual structure or su

Tutorials

When Large Vision-Language Models Meet Person Re-Identification

arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un

tutorialsarxiv-cs-cv