Search: “models”

How Small Can You Go? A Controlled Study of LoRA Rank, Target Modules, and Quantization Trade-offs for Text-to-SQL on a 60M-Parameter Model

arXiv:2607.25583v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) and low-bit quantization are now standard tools for adapting language models under tight compute budgets, yet the

29 Jul 2026

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Mage-VL: An Efficient Codec-Native Streaming Multimodal Foundation Model

DGX agent

arXiv:2607.24904v1 Announce Type: cross Abstract: Standard vision-language models (VLMs) suffer from Moravec's paradox: they excel at complex offline visual reasoning but struggle with simple streamin

model-releasesarxiv-cs-cl

29 Jul 2026

Raven: High-Recall Sequence Modeling with Sparse Memory Routing

arXiv:2607.25357v1 Announce Type: cross Abstract: Long-context recall in linear-time sequence models highlights a tradeoff in how they write to memory. State-based linear models, such as state-space m

29 Jul 2026

Autoregressive One-Step Generative Modeling for Dynamical System Forecasting

arXiv:2605.05540v2 Announce Type: replace Abstract: Fast surrogate modeling for high-dimensional physical dynamics requires more than low short-term error: useful models must roll out efficiently whil

Hierarchical Reinforcement Learning with Optimal Level Synchronization Based on Flow-Based Deep Generative Model

arXiv:2107.08183v2 Announce Type: replace Abstract: High-dimensional state and action spaces combined with sparse reward structures in reinforcement learning (RL) environments typically require advanc

Tutorials

Like a bilingual baby: The advantage of visually grounding a bilingual language model

arXiv:2210.05487v3 Announce Type: replace Abstract: Unlike most neural language models, humans learn language in a rich, multi-sensory and, often, multi-lingual environment. Current language models ty

tutorialsarxiv-cs-cl

Moving-Horizon Estimation and Nonlinear Model Predictive Control of Cable-Driven Soft Manipulators

arXiv:2607.24029v1 Announce Type: new Abstract: Precise control of soft manipulators remains challenging due to the difficulty of developing accurate yet computationally tractable models for model-bas

researcharxiv-cs-ro

Real-Time Human-Centric World Modeling for Upper-Body Human-Object Interaction

arXiv:2607.23517v1 Announce Type: new Abstract: We present a real-time human-centric world model for upper-body interactive generation, aiming to synthesize coherent local world dynamics centered on a

local-aiarxiv-cs-cv

SQBench: A Benchmark for Evaluating Task Delivery by Language-Model Agents in Production-Oriented Workflows

arXiv:2607.23123v1 Announce Type: new Abstract: Existing evaluations of large language models cover knowledge, reasoning, coding, and tool use, but they rarely treat a verifiable deliverable produced

Quantum Spectral Model: Data Reuploading with Input-Conditioned Frequency Support

arXiv:2607.22516v1 Announce Type: cross Abstract: A central design principle in modern machine learning and artificial intelligence is to align a model's inductive bias with the structure of its input

local-aiarxiv-cs-lg

27 Jul 2026

Black box behavioural modelling: Predicting human activity schedules with a deep conditional generative approach

arXiv:2512.04223v2 Announce Type: replace Abstract: Modelling the complexity and diversity of human activity scheduling behaviour is inherently challenging. We demonstrate ActVAE, a deep conditional-g

24 Jul 2026

Wisdom of LLM Crowds: Aggregation and Contamination in Language Model Ensembles

arXiv:2607.18269v2 Announce Type: replace Abstract: The wisdom of crowds -- the finding that aggregating judgments across individuals often outperforms the best individual -- has been extensively stud

local-aiarxiv-cs-ai

24 Jul 2026

WorldPack: Dynamic Frame Compression for Long-context Video World Modeling

arXiv:2512.02473v2 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on p

23 Jul 2026

Design, Modeling and Experimental Validation of a Miniature Hybrid Underwater Glider With Large-Range Foldable Deflectable Wings

model-releasesarxiv-cs-ro

arXiv:2607.13622v1 Announce Type: new Abstract: Miniature hybrid underwater gliders have attracted increasing attention for long-endurance ocean observation and confined-space inspection. Large-range

Lag Operator SSMs: A Geometric Framework for Structured State Space Modeling

arXiv:2512.18965v2 Announce Type: replace Abstract: Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. H

VAIOM: Continuous-Input, Discrete-Output Decoder-Only Financial Sequence Modeling

arXiv:2607.13929v1 Announce Type: new Abstract: Financial observations are continuous, heterogeneous, and noisy, whereas decoder-only next-token models are usually built around discrete symbolic input

Where Should RL Post-Training Compute Go? Model Size, Search, Learning, and Feedback

arXiv:2607.13389v1 Announce Type: new Abstract: Reinforcement Learning (RL) post-training is increasingly used to adapt foundation models for reasoning, planning, and feedback-driven robot-learning pi

safetyarxiv-cs-lg

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task

arXiv:2510.18315v2 Announce Type: replace-cross Abstract: We investigate how embedding dimension affects the emergence of an internal 'world model' in a transformer trained with reinforcement learning

15 Jul 2026

The Model Knows Your Project, Not You: Measuring Recognition in LLMs with NameRank

arXiv:2607.12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human see

15 Jul 2026

Anatomically Guided Latent Diffusion for Brain MRI Progression Modeling

arXiv:2601.14584v2 Announce Type: replace Abstract: Accurately modeling longitudinal brain MRI progression is crucial for understanding neurodegenerative diseases and predicting individualized structu

researcharxiv-cs-cv

10 Jul 2026

Stop Guessing When to Stop Testing: Efficient Model Evaluation with Just Enough Data

arXiv:2607.08522v1 Announce Type: new Abstract: The inherent rigidity of fixed-size benchmarks makes them an inefficient tool for model evaluation. Diverse evaluation objectives, including model ranki

10 Jul 2026

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

arXiv:2607.08375v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition o

10 Jul 2026

Grounding Spatial Relations in a Compact World Model: Instruction Leakage and a Goal-Free Dynamics Fix

arXiv:2607.06925v1 Announce Type: new Abstract: Compact world models that condition on a language goal promise to ground relations such as ``put the red block left of the blue block'' using a sparse s

Large Behavior Model: A Promptable Digital Twin of the Retail Customer

arXiv:2607.06993v1 Announce Type: new Abstract: Customer behavior modeling underpins recommendation, marketing, and decision support, yet existing approaches either optimize predictive accuracy withou

LLM-powered reasoning in agent-based modeling

arXiv:2607.06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making. However, ABMs

Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning

arXiv:2511.13726v2 Announce Type: replace-cross Abstract: We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the fina

Imagined Rollouts are Kinematic, Not Dynamic: A Diagnosis of Long-Horizon World-Model Failure

model-releasesarxiv-cs-ro

arXiv:2607.05966v1 Announce Type: new Abstract: Long-horizon failure in world models is conventionally attributed to compounding error, a generic framing that does not distinguish what kind of error c

8 Jul 2026

Agents

Unicode TAG-Block Concealment of Tool-Metadata Payloads in the Model Context Protocol: An Approval-View Fidelity Gap Across Three Independent Server Implementations

arXiv:2607.05744v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is the dominant way coding agents discover and invoke external tools. A server advertises each tool through a tools/l

agentsarxiv-cs-ai

8 Jul 2026

Curriculum-Guided Layer Scaling for Language Model Pretraining

model-releasesarxiv-cs-cl

arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr

Efficient Decentralized Multi-task Dataset Valuation via Model Merging

arXiv:2607.03346v1 Announce Type: cross Abstract: Accurate and efficient dataset valuation is essential for enabling fair and transparent data marketplaces, especially when multiple contributors provi

LLM-Assisted Semantic Alignment and Integration in Collaborative Model-Based Systems Engineering Using SysML v2

arXiv:2508.16181v2 Announce Type: replace-cross Abstract: Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across inde

Object-Centric Environment Modeling for Agentic Tasks

arXiv:2607.02846v1 Announce Type: new Abstract: Large language model (LLM) agents can improve through accumulated experience, but free-form textual memories become difficult to maintain, validate, and

local-aiarxiv-cs-ai

Poisson-Gamma Modeling of Inter-Relational Dependencies in Dynamic Knowledge Graphs

arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, social relationships, and language information

SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation

model-releasesarxiv-cs-cv

arXiv:2603.19873v2 Announce Type: replace Abstract: Fine-tuning foundation models for Earth Observation is computationally expensive, with high training time and memory demands for both training and d

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

arXiv:2511.15684v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation

model-releasesarxiv-cs-cl

arXiv:2607.02182v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence,

3 Jul 2026

MEPA: Multi-Scale Representation Alignment for Visual Autoregressive Modeling with Mixture of Experts

arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities

2 Jul 2026

Predicting LLM Reasoning Performance with Small Proxy Model

arXiv:2509.21013v4 Announce Type: replace-cross Abstract: Given the prohibitive cost of pre-training large language models, it is essential to leverage smaller proxy models to optimize datasets before

2 Jul 2026

Citation Discipline in Spec-Driven Development: A Cross-Model Empirical Study of Output Determinism and Automated Hallucination Detection in LLM-Generated Code

arXiv:2606.30689v1 Announce Type: cross Abstract: Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ funda

Diffusion-warm sampling of the XY model enables fast thermalization at scale

arXiv:2606.30773v1 Announce Type: cross Abstract: We introduce a novel technique for scalable sampling of spin-system states with continuous symmetries using diffusion models. By applying our approach

LightOnOCR: A 1B End-to-End Multilingual Vision-Language Model for State-of-the-Art OCR

model-releasesarxiv-cs-cv

arXiv:2601.14251v2 Announce Type: replace Abstract: We present LightOnOCR-2-1B, a 1B-parameter end-to-end multilingual vision--language model that converts document images (e.g., PDFs) into clean, nat

Long-term Traffic Simulation via Structured Autoregressive Modeling

arXiv:2606.31209v1 Announce Type: new Abstract: Interactive traffic simulation is a vital world model for autonomous driving. A central challenge in long-horizon simulation is modeling sustained multi

Modeling Cell-Cycle-Aware Single-Cell Drug Perturbation Responses

arXiv:2606.30695v1 Announce Type: cross Abstract: Single-cell drug perturbation models should predict not only transcriptional response magnitude, but also whether a treatment alters the proliferative

Predictable GRPO: A Closed-Form Model of Training Dynamics

arXiv:2606.30789v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a standard tool for improving the reasoning ability of large language models, yet its training dyna

Attractor States Emerge in Multi-Turn LLM Conversations

model-releasesarxiv-cs-cl

arXiv:2606.30571v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in open-ended multi-agent settings, but the long-run dynamics of model--model interaction remain po

Do We Still Need Fine Tuning? Turkish Sentiment Analysis in the Era of Large Language Model

arXiv:2606.29614v1 Announce Type: cross Abstract: This study examines whether supervised fine-tuning remains necessary for Turkish sentiment analysis in the era of large language models. We compare cl

FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation

arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp

safetyarxiv-cs-ro

HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data

arXiv:2606.29784v1 Announce Type: cross Abstract: Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these 'gold' labels are expensive to collect