Search: “models”

KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering

arXiv:2607.22652v1 Announce Type: new Abstract: Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream know

agentsarxiv-cs-ai

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LOCUS: Local Visual Cue Search for Enhancing Fine-Grained Perception in Multimodal Large Language Models

DGX agent

arXiv:2606.16586v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) remain unreliable on fine-grained visual perception, even when high-resolution inputs preserve the necessar

local-aiarxiv-cs-cv

28 Jul 2026

MM-ShiftKV: Decode-Aware Prefill-Stage KV Selection for Multimodal Large Language Models

arXiv:2607.22586v1 Announce Type: new Abstract: Key-Value (KV) caching is essential for efficient inference in multimodal large language models (MLLMs), yet its memory footprint grows linearly with co

researcharxiv-cs-ai

Not All LLM Reasoning is Visible in the Chain-of-Thought

arXiv:2607.22925v1 Announce Type: cross Abstract: A key question for AI safety is whether a language model expresses all of its reasoning in its output tokens. We demonstrate a concrete failure mode w

Operational Proto-Introspection in Looped Language Models: Process-Quality Taps, Executable Branching, and the Readout-Control Boundary

arXiv:2607.18553v2 Announce Type: replace-cross Abstract: Can a language model read the quality of its ongoing computation, and can an external intervention turn that readout into better outcomes? We

researcharxiv-cs-ai

Parallel Tokenizers: Rethinking Encoder Models' Vocabulary Design in Cross-Lingual Transfer of Low-Resource Languages

arXiv:2510.06128v2 Announce Type: replace Abstract: Tokenization forms the basis of multilingual language models, yet existing methods often limit cross-lingual transfer by mapping semantically equiva

safetyarxiv-cs-cl

PerturbPFN: Probing the Limits of Synthetic Priors in Drug Perturbation Modelling

arXiv:2607.23447v1 Announce Type: new Abstract: Predicting cellular responses to unseen chemical perturbations is challenging due to unknown targets and mechanisms, high-dimensional expression respons

Local Ai

RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models

arXiv:2607.24447v1 Announce Type: new Abstract: On-Policy Self-Distillation (OPSD) uses privileged information available only to the teacher to provide dense token-level supervision on trajectories ge

local-aiarxiv-cs-cv

SARATR-X-v2: Scale-Aware Structural Pre-Training for SAR Foundation Models

arXiv:2607.23238v1 Announce Type: new Abstract: Masked image modeling has become a dominant paradigm for SAR pre-training, yet the design of the reconstruction target remains fundamentally unsettled.

Segmentation Robustness and Predictive Utility in Glioblastoma Radiomics: Evidence for a Trade-off in Survival Modelling

arXiv:2607.23626v1 Announce Type: cross Abstract: Radiomic biomarkers derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive tools for tumor characterization and p

WCM: World-Cognition Model for Generalizable Human-Robot Interaction

arXiv:2607.22999v1 Announce Type: cross Abstract: Language agents can now interact fluently with users in software, but robots still struggle to bring comparable interaction to physical tasks. Current

agentsarxiv-cs-ai

Tutorials

When Activation Oracles Learn Not to Read: Concept-Specific Blind Spots in Fine-Tuned Oracles

arXiv:2607.23379v1 Announce Type: cross Abstract: Activation Oracles (AOs) are language models trained to answer natural-language questions about another model's internal activations. They offer a fle

tutorialsarxiv-cs-ai

Tutorials

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature

arXiv:2510.05416v3 Announce Type: replace Abstract: Differentially private stochastic gradient descent (DP-SGD) offers the promise of training deep learning models while mitigating many privacy risks.

tutorialsarxiv-cs-lg

Tutorials

GeoDiff-SAR: A Geometric Prior Guided Diffusion Model for SAR Image Generation

arXiv:2601.03499v2 Announce Type: replace-cross Abstract: Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains

tutorialsarxiv-cs-cv

Low-Altitude Channel Multipath Prediction via Panoramic Perception and Vision-Language Model

arXiv:2607.21953v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) communication is expected to support a wide range of low-altitude applications in 6G mobile networks. However, traditional

Opaque Epistemic Mediation: How LLM Deployment Configurations Shape the Validation of Pseudo-Science

model-releasesarxiv-cs-cl

arXiv:2607.22513v1 Announce Type: cross Abstract: Commercial large language models are increasingly used as knowledge references, yet their stance on contested scientific claims is neither stable nor

Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases

arXiv:2602.09572v3 Announce Type: replace-cross Abstract: The purpose of predictive modeling on relational data is to predict future or missing values in a relational database, for example, future pur

Hardware

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention

arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus

hardwarearxiv-cs-lg

Agree on the Model, Verify the Inference: GKR Protocols for HND-Based Transformer Inference

arXiv:2607.21162v1 Announce Type: new Abstract: Outsourced Transformer inference exposes clients to model substitution and incomplete execution, while direct replay removes the computational benefit o

Attention Degradation, Function Token Anchoring, and the Limits of Attention-Based Intervention in Large Language Models

arXiv:2607.20524v1 Announce Type: new Abstract: Mean cross-positional attention degradation is widely reported in transformer interpretability, yet whether it causally limits contextual retrieval rema

FA-LAM: Focus-Aware Large Avatar Model for One-Shot 4D Animatable Gaussian Head

arXiv:2607.20922v1 Announce Type: new Abstract: We propose FA-LAM, a Focus-Aware Large Avatar Model for one-shot animatable Gaussian head creation, while simultaneously enabling static 3D and dynamic

From a Word-Level Dictionary to Sentence-Level Semantics: Multilingual Grievance Labelling with Contextual Models

model-releasesarxiv-cs-cl

arXiv:2607.20946v1 Announce Type: new Abstract: Grievance is one of the warning signs analysts look for when assessing threats of violence. It is increasingly measured at scale from online text, most

Generative Artificial Intelligence in Bioinformatics: A Systematic Review of Models, Applications, and Methodological Advances

arXiv:2511.03354v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is transforming bioinformatics by advancing genomics, proteomics, transcriptomics, structural biolo

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

arXiv:2607.21085v1 Announce Type: new Abstract: Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatia

GeoWorldAD: Geometry World Action Model for Autonomous Driving

arXiv:2607.17521v2 Announce Type: replace Abstract: Autonomous driving requires both safe and efficient planning decisions in dynamic 3D environments. Although recent Vision/Video-Action models learn

safetyarxiv-cs-ro

Naver-News-KO: A Korean News Summarization Dataset for Open-Source Fine-Tuning of Summarization Models

model-releasesarxiv-cs-cl

arXiv:2607.20442v1 Announce Type: new Abstract: We release Naver-News-KO, a Korean news summarization dataset of 27,400 (document, summary) pairs collected from Naver News over a ten-day window in Jul

news-crawler-LM: A Small Long-Context Model For High-Quality News Crawling

arXiv:2607.21284v1 Announce Type: new Abstract: Extracting structured content from news pages remains challenging due to heterogeneous HTML layouts, inconsistent markup, and substantial boilerplate su

researcharxiv-cs-cl

SuperFlow: Training Flow Matching Models with RL on the Fly

arXiv:2512.17951v3 Announce Type: replace Abstract: Recent progress in flow-based generative models and reinforcement learning (RL) has improved text-image alignment and visual quality. However, curre

safetyarxiv-cs-cv

Texture++: Elevating 3D Asset Texture Resolution with a Region-Aware Diffusion Model

arXiv:2607.21504v1 Announce Type: new Abstract: Numerous 3D assets are discarded due to low texture resolution, while current super-resolution models ignore texture maps and focus on natural images. A

A Bayesian Framework for Built-in Input Dimension Reduction for Gaussian Process Modeling

arXiv:2607.19498v1 Announce Type: cross Abstract: Gaussian process (GP) modeling is widely used in computational science and engineering. However, fitting a GP to high-dimensional inputs remains chall

Bounding Boxes to Improve Small Language Model Performance on Vision-Based Grading Tasks

arXiv:2607.18767v1 Announce Type: new Abstract: The deployment of Small Language Models (SLMs) in educational settings offers significant advantages in terms of privacy, cost, and scalability. However

D3VL: Understanding Driving Scenes from 3D Time Series Data and Video with Language Models

arXiv:2607.19528v1 Announce Type: cross Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have triggered the development of end-to-end MLLMs for autonomous driving. However, the ma

Dreamer-CPC: Message Learning with World Models for Decentralized Multi-agent Reinforcement Learning

arXiv:2607.19809v1 Announce Type: cross Abstract: In multi-agent reinforcement learning (MARL), inter-agent communication is effective for improving performance under partial observability. Representa

agentsarxiv-cs-lg

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

arXiv:2607.18958v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulne

safetyarxiv-cs-cv

Efficient Chain-of-Modality Reasoning via Progressive Compression for Spoken Language Models

arXiv:2607.19932v1 Announce Type: new Abstract: Spoken language models (SLMs) enable natural human-computer interaction, but their reasoning ability still lags behind that of text-based large language

researcharxiv-cs-cl

JAGG: Jacobian-Aggregated Group Gradient for Efficient GRPO Training of Diffusion Models

arXiv:2607.17572v2 Announce Type: replace Abstract: Group Relative Policy Optimization (GRPO) is a powerful reinforcement learning algorithm for aligning generative models with human preferences. Whil

safetyarxiv-cs-lg

Leveraging Offline Supervision for Efficient and Generalizable Reinforcement Learning in Large-Scale Vision-Language-Action Models

arXiv:2607.19399v1 Announce Type: cross Abstract: It is commonly observed that online reinforcement learning (RL) produces better-performing strategies than offline methods across a broad range of per

Multi-Mask Diffusion Language Models for Few-Step Generation

arXiv:2607.19686v1 Announce Type: new Abstract: Masked diffusion models (MDMs) are a promising family of language generators, but achieving high-quality few-step generation remains challenging. In MDM

researcharxiv-cs-cl

Multimodal Large Language Models for Remote Sensing Image Understanding: Domain-Specific or General-Purpose?

arXiv:2607.20284v1 Announce Type: new Abstract: The rapid development of multimodal large language models (MLLMs) has introduced a flexible paradigm for remote sensing image scene understanding (RSISU

Predictive Extrema, Unprofitable Policies: An AI-Assisted Audit of Candle-Based Binance Spot Timing Models

arXiv:2607.19453v1 Announce Type: cross Abstract: We audit whether candle-based machine-learning models can turn predictions of cryptocurrency extrema or short-horizon outcomes into positive Binance S

Predictive single cell foundation model for gene regulation and aging with privacy-preserving tabular learning

arXiv:2607.19400v1 Announce Type: new Abstract: Pre-trained foundation models (FMs) have begun transforming single-cell genomics, but scaling them raises privacy concerns. Moreover, unlike text data,

agentsarxiv-cs-lg

Prompt Programming for Cultural Bias and Alignment of Large Language Models

arXiv:2603.16827v2 Announce Type: replace Abstract: Culture shapes reasoning, values, prioritization, and strategic decision-making, yet large language models (LLMs) often exhibit cultural biases that

RPPNet: Perceptually-Grouped Rhythm-Pitch Primitives for Long-Term Structure Melody Generation via Boundary-Aware Modeling

arXiv:2607.19776v1 Announce Type: cross Abstract: Existing symbolic music generation models typically use bars as the basic structural unit. However, human perception of musical phrases often does not

researcharxiv-cs-ai

A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions

model-releasesarxiv-cs-cv

arXiv:2601.22830v2 Announce Type: replace Abstract: Reliable environmental perception remains one of the main obstacles for safe operation of automated vehicles. Safety of the Intended Functionality (

Ask Before You Diagnose: Safe-Psych, a Sequential Evaluation Benchmark for LLMs in Psychiatry

arXiv:2607.13036v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for decision support in healthcare, but clinical evidence is often incomplete or evolving. When the

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System

arXiv:2607.13608v1 Announce Type: new Abstract: Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computat

agentsarxiv-cs-ai

Beyond Color Geometry: Evaluating Human-Like Color Representations in Vision Models

arXiv:2607.13647v1 Announce Type: cross Abstract: Do vision models see colors the way humans do? Existing evaluations of color representations usually compare them with geometric spaces such as CIELAB

Ego-Dynamics-Augmented World Model for Autonomous Driving with Zero-Shot Cross-Chassis Adaptation

arXiv:2607.13410v1 Announce Type: new Abstract: World model (WM)-based reinforcement learning enables sample-efficient end-to-end autonomous driving learning by imagining long-horizon trajectories in

agentsarxiv-cs-ro