Search: “models”

Quaternion Tensor Modeling for Joint Color-Polarization Demosaicking

arXiv:2608.02144v1 Announce Type: new Abstract: Division-of-focal-plane (DoFP) color polarization cameras enable snapshot acquisition of color polarization mosaic images, but the inherently sparse sam

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Model Releases

Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks

DGX agent

arXiv:2608.02442v1 Announce Type: cross Abstract: Scientific reasoning benchmarks typically evaluate large language models (LLMs) using final-answer accuracy. However, a correct answer does not necess

model-releasesarxiv-cs-cl

4 Aug 2026

Local Ai

Roomer: Reflective Object-Grounded Model Editing and Repair for 3D Indoor Layout Synthesis

arXiv:2608.01973v1 Announce Type: cross Abstract: Existing indoor layout generators produce globally plausible layouts yet may retain local violations such as collisions, out-of-bounds placements, obs

local-aiarxiv-cs-cv

Seeing the Unseen: Towards Training-Free Inspection for Wind Turbine Blades Using Knowledge-Augmented Vision Language Models

arXiv:2510.22868v2 Announce Type: replace Abstract: Wind turbine blades operate in harsh environments, making timely damage detection essential for preventing failures and optimizing maintenance. Dron

SPIRIT: Spatio-temporal Pairwise Relational Modeling of Instrument-Tissue Interactions for Surgical Action Triplet Recognition

arXiv:2608.02188v1 Announce Type: new Abstract: Fine-grained understanding of surgical activity is essential for context-aware assistance in the operating room, including safety monitoring, adverse ev

safetyarxiv-cs-cv

Surrogate Modeling for the Design of Optimal Lattice Structures using Tensor Completion

arXiv:2510.07474v2 Announce Type: replace Abstract: When designing new materials, it is often necessary to design a material with specific desired properties. Unfortunately, as new design variables ar

researcharxiv-cs-lg

SVGEval: A Vision-Grounded Framework for Perceptual-Quality Benchmarking and Evaluation in Text-to-SVG Generation

model-releasesarxiv-cs-cv

arXiv:2608.01977v1 Announce Type: new Abstract: Multimodal large models are increasingly used to generate scalable vector graphics (SVG), but reliable evaluation remains underexplored. Existing protoc

TabDPT-Turbo: Efficient In-Context Learning for Tabular Prediction

arXiv:2608.01400v1 Announce Type: new Abstract: Tabular foundation models, driven by in-context learning, have rapidly grown in quality and popularity. However, recent approaches with either cell-base

Training nGPT

arXiv:2608.01284v1 Announce Type: new Abstract: The normalized Transformer (nGPT) realizes hyperspherical representation learning by constraining model parameter vectors and activation vectors to the

Visualising Information Flow in Word Embeddings with Diffusion Tensor Imaging

arXiv:2601.05713v2 Announce Type: replace Abstract: Understanding how large language models (LLMs) represent natural language is a central challenge in natural language processing (NLP) research. Many

When May a Model Replace the Experiment? Audits, Licenses, and the Price of Trust in Surrogate-Driven Design

arXiv:2608.01378v1 Announce Type: new Abstract: Design campaigns in chemistry, materials science, and machine learning share a bottleneck: determining how good a candidate truly is requires an expensi

safetyarxiv-cs-lg

Tutorials

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

tutorialsarxiv-cs-ai

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und

ReLoop-UME: Recurrent Depth with Learnable Retrieval Registers for Universal Multimodal Embedding

model-releasesarxiv-cs-cv

arXiv:2607.28751v1 Announce Type: new Abstract: Universal multimodal embedding (UME) maps heterogeneous multimodal inputs into a shared embedding space. Existing UME models either form embeddings thro

The Grokked Illusion: True Equilibrium Mitigates Catastrophic Forgetting

arXiv:2607.29503v1 Announce Type: new Abstract: While neural networks are typically evaluated by their training and test performance, these metrics do not reveal how robust a learned representation is

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

Tokenizer-Agnostic Engram Module

arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relie

Can Agents Deceive? Evaluating Reasoning and Deception in ParliamentBench using a Social Deduction Game

arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil

IGME: Efficient Chained Method Ensemble for Transferable Semantic Segmentation Attacks

arXiv:2607.27465v1 Announce Type: new Abstract: Semantic segmentation models are vulnerable to transferable adversarial perturbations, yet evaluating transfer attacks on dense prediction models can be

Latent-Kernel Discrete Flow Maps for Few-Step Generation

arXiv:2607.27529v1 Announce Type: new Abstract: Discrete diffusion and flow-matching models denoise a sequence over many steps, but to keep each step cheap, they factorize the transition across positi

researcharxiv-cs-lg

MORFES: A Benchmark for Productive Inflectional Competence in Modern Greek

arXiv:2607.28274v1 Announce Type: new Abstract: Modern Greek is a richly inflected language, yet the language models built for it are evaluated mainly on factual knowledge, and no benchmark is dedicat

Applications

Scalable Drift Monitoring in Medical Imaging AI

arXiv:2410.13174v3 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model

applicationsarxiv-cs-cv

Sympathetic Framing: Evaluating AI Alignment across Sociodemographic Groups

arXiv:2607.27232v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly shaping how we consume information and form our worldview. This raises concerns beyond bias in AI: do LLMs

Hardware

Understanding Is Done Early: A Depth Division of Labor in Large Language Models and Its Use for Unbounded-Context Memory

arXiv:2607.28263v1 Announce Type: new Abstract: Transformer depth is not used uniformly: lower and middle layers build semantic representations, while upper layers increasingly specialize them for pre

hardwarearxiv-cs-cl

Zero-Shot Face-to-Speech Synthesis via Latent Space Adaptation of a Style-Diffusion TTS Model

arXiv:2607.26742v1 Announce Type: cross Abstract: Zero-shot text-to-speech (TTS) clones a voice from a short audio prompt, but this reliance on reference audio is a barrier when only visual informatio

CheckVLA: Execution-Time Verification with Action-Conditioned World Model for Long-Horizon Mobile Manipulation

arXiv:2607.26789v1 Announce Type: new Abstract: Vision-language-action (VLA) policies commonly execute long-horizon mobile manipulation through open-loop action chunks, issuing multiple actions withou

safetyarxiv-cs-ro

ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information

arXiv:2106.16038v3 Announce Type: replace Abstract: Recent pretraining models in Chinese neglect two important aspects specific to the Chinese language: glyph and pinyin, which carry significant synta

Cognitive Convergence: Deep Similarities Between Large Language Models and Human Cognition

arXiv:2607.26179v1 Announce Type: cross Abstract: LLMs are widely regarded as alien intelligences, systems whose cognitive operations are fundamentally unlike our own. Apparent similarities to human c

GEqTrain: A Configuration-Driven Framework for Retargeting Equivariant Graph Neural Networks Across 3D Scientific Tasks

arXiv:2607.19083v2 Announce Type: replace Abstract: Equivariant graph neural networks provide a powerful modeling language for three-dimensional scientific data, but their reuse is often limited by im

Local Ai

Origins and mitigation of double descent in reduced order modeling

arXiv:2607.26414v1 Announce Type: cross Abstract: Latent low-dimensional structure in datasets of natural and engineered systems enables their sparse sensing, or full-state reconstruction from histori

local-aiarxiv-cs-lg

Post-Training at the Edge of Detectability: A Game-Theoretic Approach to Fine-Tuning

arXiv:2607.26358v1 Announce Type: new Abstract: Reinforcement learning (RL) fine-tuning is widely used in language model training to improve model performance on a target task while limiting drift fro

Prosody-driven Jailbreaks in Audio LLMs: A Controlled Study and Mechanistic Analysis

arXiv:2607.26541v1 Announce Type: cross Abstract: Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains uncle

SERPO: Self-Evolving Rubric Policy Optimization for Open-Ended Test-Time Reinforcement Learning

arXiv:2607.26873v1 Announce Type: new Abstract: Test-time reinforcement learning (TTRL) enables language models to self-evolve at inference time without labeled feedback. Existing methods rely on answ

Cinematic Compositing Using Character-Environment-Harmonized Video Generation Models

arXiv:2606.20233v2 Announce Type: replace Abstract: Cinematic compositing aims to integrate green-screen characters into novel environments while maintaining physical and photometric realism. Previous

CycleVLA: Proactive Self-Correcting Vision-Language-Action Models via Subtask Backtracking and Minimum Bayes Risk Decoding

arXiv:2601.02295v2 Announce Type: replace Abstract: Current work on robot failure detection and correction typically operates in a post hoc manner, analyzing errors and applying corrections only after

researcharxiv-cs-ro

DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space

arXiv:2607.25675v1 Announce Type: new Abstract: Text-space optimization adapts large language models (LLMs) by editing external natural-language artifacts rather than model weights, so the optimized a

Evaluating Multi-Turn Multimodal Diagnostic Reasoning on Challenging Real-World Clinical Cases

arXiv:2607.25933v1 Announce Type: cross Abstract: Clinical diagnostic evaluation should not only assess whether models can provide correct diagnoses, but also reflect the realities of clinical practic

Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales

arXiv:2607.25364v1 Announce Type: new Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection

safetyarxiv-cs-ai

Fast, accurate, and differentiable: a neural-network surrogate for NRSur7dq4 precessing binary black hole waveforms

arXiv:2607.24960v1 Announce Type: cross Abstract: We present a neural network surrogate model that emulates the NRSur7dq4 gravitational waveform model for precessing binary black hole mergers. The sur

Finding Optimal Cost-Bounded Plan Reductions: Refined Model

arXiv:2607.25484v1 Announce Type: new Abstract: In some real applications a plan may later become unfeasible due to newly imposed budget constraints, yet, at the same time, using only the original act

Kernel Forge: An Agent Harness for LLM-based Generation and Optimization of CUDA Kernels

arXiv:2607.24762v1 Announce Type: new Abstract: Machine learning models are increasingly embedded in everyday software, and most of their runtime is spent in a small set of compute kernels such as mat

Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation

arXiv:2607.25956v1 Announce Type: new Abstract: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matche

safetyarxiv-cs-ai

Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model

arXiv:2510.22863v2 Announce Type: replace-cross Abstract: Reliable long-term forecasting of PM2.5 concentrations is critical for public health early-warning systems, yet existing deep learning approac

Measuring the State of Open Science in Transportation Using Large Language Models

arXiv:2601.14429v2 Announce Type: replace-cross Abstract: Open science initiatives have strengthened scientific integrity and accelerated research progress across many fields, but the state of their p

RIDGE: An Autonomous Framework for Validation and Method Discovery in LLM-Generated Option Pricing

arXiv:2607.25199v1 Announce Type: cross Abstract: Automated code generation is becoming an important tool in quantitative finance, where large language models can generate option pricing implementatio

RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement

arXiv:2607.25886v1 Announce Type: cross Abstract: Recursive self-improvement requires turning evidence of model failures into better models. Data-centric post-training research entails diagnosing capa

Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions

arXiv:2607.25026v1 Announce Type: cross Abstract: In this work, we present a simulation-based parameter estimation framework for a model defined by a computational simulation of a physical system. We

The Disruptive Impact of Large Language Models on Capture the Flag Competitions and the Path Toward Fair Play

arXiv:2607.25425v1 Announce Type: new Abstract: Capture the Flag (CTF) competitions are among cybersecurity's most effective training grounds, developing practical skill across cryptography, web explo

safetyarxiv-cs-ai