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How Do I Know What to Say Next? Barenholtz's Autogenerative Theory as an Enrichment of Harrisean Integrationism

arXiv:2607.07891v1 Announce Type: cross Abstract: Roy Harris's Integrationist linguistics offers a compelling critique of the referentialist tradition embedded deep at the heart of computational appro

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HSA: Hierarchical Slot Attention for Multi-granularity Scene-Decomposition

DGX agent

arXiv:2607.08249v1 Announce Type: new Abstract: Slot attention is a powerful framework for object-centric learning, decomposing visual scenes into latent slots through iterative competitive attention.

safetyarxiv-cs-cv

10 Jul 2026

HumanForge: A Human-Centric Deepfake Video Benchmark with Multi-Agent Forgery Rationales

arXiv:2607.08705v1 Announce Type: new Abstract: Rapid advancements in video diffusion models and temporal editing tools have enabled the generation of highly realistic human-centric videos, posing unp

ICDAR 2026 HIPE-OCRepair Competition on LLM-Assisted OCR Post-Correction for Historical Documents

arXiv:2607.08143v1 Announce Type: cross Abstract: We present the results of HIPE-OCRepair-2026, an ICDAR competition on LLM-assisted OCR post-correction of historical documents. OCR post-correction re

Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation

arXiv:2607.08758v1 Announce Type: new Abstract: Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biol

Agents

Idiobionics: The Unification of Privacy and Intelligent Robotic Prostheses

arXiv:2607.07775v1 Announce Type: new Abstract: The human body is at the center of a growing family of technologies designed to tightly and persistently couple biological and digital systems. Robotic

agentsarxiv-cs-ai

IFAR: Multi-Perspective and Multi-Level Causal Discovery with LLMs

arXiv:2409.05559v2 Announce Type: replace Abstract: Large language models (LLMs) have developed rapidly, and their reasoning capabilities have become a hot research topic. However, there is still limi

Hardware

Image classification via a quantum-inspired strategy involving a mixture of experts

arXiv:2607.07754v1 Announce Type: new Abstract: Pattern recognition problems arise in a variety of physical image processing situations, and convolutional neural networks are a popular scheme for the

hardwarearxiv-cs-lg

IMProofBench: Benchmarking AI on Research-Level Mathematical Proof Generation

model-releasesarxiv-cs-cl

arXiv:2509.26076v2 Announce Type: replace Abstract: As the mathematical capabilities of large language models (LLMs) improve, it becomes increasingly important to evaluate their performance on researc

Improving Ad-hoc Search Effectiveness for Conversational Information Retrieval via Model Merging

model-releasesarxiv-cs-cl

arXiv:2607.08540v1 Announce Type: cross Abstract: Conversational information retrieval is challenging since it requires the consideration of the conversation history which potentially gives rise to to

Applications

Improving Engine Sound Analysis in Hot-Test Environments via a RAB-U-Net (Residual Attention Block U-Net) Noise Removal Method

arXiv:2606.21887v2 Announce Type: replace-cross Abstract: During hot tests on a production line, engine-sound analysis is crucial to ensuring product quality and performance. However, background noise

applicationsarxiv-cs-ai

Improving RCT-Based Treatment Effect Estimation Under Covariate Mismatch via Calibrated Alignment

arXiv:2603.19186v3 Announce Type: replace Abstract: Randomized controlled trials (RCTs) are the gold standard for estimating treatment effects, yet they are often underpowered for detecting effect het

safetyarxiv-cs-lg

ImputeViz: A Visual Analytics Dashboard for Diagnosing Missing Data and Comparing Imputation Methods

arXiv:2607.08579v1 Announce Type: cross Abstract: Missing data is a persistent obstacle in scientific, social science, and public health research, often biasing analyses and placing accountability on

researcharxiv-cs-lg

In vivo feasibility study of humanoid robots in surgery

arXiv:2607.07972v1 Announce Type: new Abstract: Recent advances in actuation, control and learning have rapidly pushed humanoid robots from a distant vision towards near-term real-world deployment. He

safetyarxiv-cs-ro

Infinity-Parser2 Technical Report

arXiv:2607.07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end

Input-Constrained Spatiotemporal Tubes for Safe Navigation of Unknown Euler-Lagrange Systems in Dynamic Environments

arXiv:2607.08189v1 Announce Type: cross Abstract: Safe navigation in dynamic environments is challenging when system dynamics are unknown and actuator inputs are limited. Existing methods either rely

researcharxiv-cs-ro

Instance Generation for Patient-to-room Assignment and Admission Scheduling Based on Real Hospital Data

arXiv:2507.03423v2 Announce Type: replace-cross Abstract: Developing algorithms for real-life problems that perform well in practice depends on the availability of realistic data for testing. Obtainin

researcharxiv-cs-lg

INTENT: An LSTM Framework for Vehicle Intention Prediction in Intersection Scenarios with Comprehensive Ablation Analysis

arXiv:2607.08316v1 Announce Type: new Abstract: Vehicle intention prediction is a pivotal aspect in the agility and safety of autonomous vehicles in all driving scenarios; if genuine enhancement of au

It Takes a MAESTRO To Prune Bad Experts

arXiv:2607.08601v1 Announce Type: new Abstract: Sparsely-activated Mixture-of-Experts (MoE) language models achieve remarkable inference efficiency by activating only a small fraction of parameters pe

safetyarxiv-cs-cl

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl

Joint Bayesian Parameter and Model Order Estimation for Low-Rank Probability Mass Tensors

arXiv:2410.06329v4 Announce Type: replace-cross Abstract: Obtaining a reliable estimate of the joint probability mass function (PMF) of a set of random variables from observed data is a significant ob

Joint Discrete-Continuous Flow Matching for Open-Vocabulary Inverse Design of Multilayer Optical Coatings

arXiv:2607.08392v1 Announce Type: cross Abstract: Amortized neural inverse design typically remains closed-world: component choices are fixed vocabulary tokens, coordinate grids are frozen at training

Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom

arXiv:2607.07851v1 Announce Type: cross Abstract: We give mathematically self-contained formulations, in the complex-time (kime) representation, of three open problems from the foundations of classica

Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences

arXiv:2204.04888v2 Announce Type: replace-cross Abstract: In recent years, with the continuous progress of science and technology, the number of scientific research achievements has increased rapidly.

Applications

Koopman-informed recurrent neural networks

arXiv:2410.23467v3 Announce Type: replace Abstract: Recurrent neural networks are a successful neural architecture for many time-dependent problems, including time series analysis, forecasting, and mo

applicationsarxiv-cs-lg

KronQ: LLM Quantization via Kronecker-Factored Hessian

arXiv:2607.07964v1 Announce Type: new Abstract: Post-training quantization (PTQ) is a widely adopted technique for compressing large language models (LLMs) without retraining. Existing second-order PT

Large-Language-Models-as-a-Judge in Theory-Agnostic Adaptive Metric-Alignment for Prototypical Networks in Personality Recognition

arXiv:2607.08374v1 Announce Type: cross Abstract: Personality recognition has traditionally been constrained by theory-dependent formulations, where models are trained to fit predefined psychological

Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference

arXiv:2607.08724v1 Announce Type: new Abstract: Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a sim

safetyarxiv-cs-lg

Local Ai

LDFE: Laplacian Decoupled Feature Enhancement Block for Dual-Stream CNN-based RGB-IR Object Detection

arXiv:2607.08076v1 Announce Type: cross Abstract: The complementary information between RGB and IR images can significantly enhance object detection performance under extreme conditions. Existing meth

local-aiarxiv-cs-ai

Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups

arXiv:2607.08735v1 Announce Type: new Abstract: Modern robotic perception increasingly involves large-scale geometric optimization problems distributed across multiple robots or sessions. However, exi

safetyarxiv-cs-ro

Local Ai

Learning mathsf{AC}^0 under Locally Sampleable Graphical Models

arXiv:2607.08303v1 Announce Type: new Abstract: The problem of learning constant-depth circuits holds profound implications for computational learning theory. In a seminal result, by introducing the l

local-aiarxiv-cs-lg

Agents

LEEVLA: Seeing What Matters in Latent Environment Evolution for Vision-Language-Action

arXiv:2607.08182v1 Announce Type: cross Abstract: Vision-language-action (VLA) models aim to map multimodal inputs to robot actions. However, most existing approaches struggle to cover complex dynamic

agentsarxiv-cs-ai

Less Data, Faster Convergence: Goal-Driven Data Optimization for Multimodal Instruction Tuning

arXiv:2603.12478v2 Announce Type: replace Abstract: Multimodal instruction tuning is often compute-inefficient because training budgets are spread across large mixed image-video pools whose utility is

Less Is More: Reducing Token Counts Without Compromising Performance

arXiv:2506.15138v2 Announce Type: replace-cross Abstract: Tokenization directly affects the inference efficiency of large language models, since fragmented tokenization increases sequence length and g

LESV: Language Embedded Sparse Voxel Fusion for Open-Vocabulary 3D Scene Understanding

arXiv:2604.01388v2 Announce Type: replace Abstract: Recent advancements in open-vocabulary 3D scene understanding heavily rely on 3D Gaussian Splatting (3DGS) to register vision-language features into

safetyarxiv-cs-cv

Leveraging Color Naming for Image Enhancement

arXiv:2607.08185v1 Announce Type: cross Abstract: Enhancing images to make them visually appealing is a persistent challenge in computer vision. Many deep-learning methods train models on paired datas

LEXIC: Lightweight Eye-tracking eXtension via Injected Complexity

arXiv:2607.08152v1 Announce Type: cross Abstract: On the recent EyeBench benchmark, predicting reading comprehension from eye movements exposes a stark gap: text-aware models using pretrained language

LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting

arXiv:2607.08016v1 Announce Type: new Abstract: Video relighting requires balancing long-form temporal consistency with a physically grounded understanding of light transport, which depends on accurat

Linear Attention Architectures: Mechanisms, Trade-offs, and Cross-Layer Routing

arXiv:2607.07953v1 Announce Type: cross Abstract: Self-attention lets each token retrieve information from the full context, but its quadratic cost in sequence length limits training and inference at

LiST: Lipschitz Scaling Training for Robust and Calibrated Neural Networks

arXiv:2607.07745v1 Announce Type: new Abstract: While accuracy, robustness, and calibration are all essential for reliable neural networks, they are often studied separately; developing models that sa

LiteOdyssey: A Lightweight Reasoning AI Agent for Interpretable Rare-Disease Diagnosis

arXiv:2606.16149v2 Announce Type: replace Abstract: Rare disease diagnosis involves interpreting clinical and genetic findings through complex diagnostic reasoning. We investigated whether this reason

LlamaSeg: Image Segmentation via Autoregressive Mask Generation

arXiv:2505.19422v2 Announce Type: replace Abstract: We present extbf{LlamaSeg}, a visual autoregressive framework that unifies multiple image segmentation tasks via natural language instructions. By r

LLT: Local Linear Transformer for PDE Operator Learning

arXiv:2607.07718v1 Announce Type: cross Abstract: Neural operators have become a common approach for learning PDE solution maps and accelerating numerical simulations. Transformer-based neural operato

Tutorials

LOGOS: Language-guided Oriented Object Detection in Aerial Scenes

arXiv:2607.08004v1 Announce Type: new Abstract: Object detection in geospatial scenes, such as satellite and aerial imagery, poses significant challenges due to the varying orientations and densities

tutorialsarxiv-cs-cv

LongE2V: Long-Horizon Event-based Video Reconstruction, Prediction, and Frame Interpolation with Video Diffusion Models

arXiv:2607.08770v1 Announce Type: new Abstract: Recovering high-quality video from sparse event streams is a challenging task. Regression methods often blur textures, while existing generative models

safetyarxiv-cs-cv

LSRM: High-Fidelity Object-Centric Reconstruction via Scaled Context Windows

arXiv:2604.05182v2 Announce Type: replace-cross Abstract: We introduce the Large Sparse Reconstruction Model to study how scaling transformer context windows affects feed-forward 3D reconstruction. Al

LTM: Large-scale Terrain Model for Wildfire-prone Landscapes

arXiv:2607.08711v1 Announce Type: new Abstract: Accurate 3D terrain maps are essential for emergency response when assessing wildfire hazards. However, wildfire-prone regions often span vast areas whe

safetyarxiv-cs-cv

LUMI: Tokenizer-Agnostic LLM-Based Lossless Image Compression

arXiv:2607.08221v1 Announce Type: new Abstract: Large language model (LLM)-based lossless image compression methods typically represent pixel data through the native text interface of a pretrained mod