Knowledge catalogue
arXiv:2604.12913v1 Announce Type: cross Abstract: Binary decompilation is a critical reverse engineering task aimed at reconstructing high-level source code from stripped executables. Although Large L
arXiv:2604.12268v1 Announce Type: cross Abstract: Large language models (LLMs) can generate code from natural language, but the extent to which they capture intended program behavior remains unclear.
arXiv:2604.05407v2 Announce Type: replace Abstract: LLM-based code agents treat repositories as unstructured text, applying edits through brittle string matching that frequently fails due to formattin
This r/StableDiffusion post presents a community-driven visual comparison of several modern, fast text-to-image diffusion models — Flux.2 Klein 9B (a smaller, faster distillation of Flux.2 Dev availab
arXiv:2604.11991v1 Announce Type: new Abstract: Many problems in robotics require reasoning over a mix of continuous dynamics and discrete events, such as making and breaking contact in manipulation a
arXiv:2604.12312v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed as task-oriented agents in enterprise environments, ensuring their strict adherence to complex
AI and cloud technology are reshaping every corner of every industry around the world. Without our customers, who are building the future on our platform, there would be no Google Cloud. In this regul
arXiv:2604.12376v1 Announce Type: cross Abstract: When LLM conversations grow beyond the context window, old content must be evicted -- but how does the model recover it when needed? We propose cooper
Release: datasette 1.0a27 Two major changes in this new Datasette alpha. I covered the first of those in detail yesterday - Datasette no longer uses Django-style CSRF form tokens, instead using modern
arXiv:2511.02627v2 Announce Type: replace Abstract: We introduce DecompSR, decomposed spatial reasoning, a large benchmark dataset (over 5m datapoints) and generation framework designed to analyse com
arXiv:2604.12486v1 Announce Type: new Abstract: Long-horizon collaborative vision-language navigation (VLN) is critical for multi-robot systems to accomplish complex tasks beyond the capability of a s
Google DeepMind, Alphabet Inc.’s artificial intelligence research division, Tuesday introduced a new foundation robotics AI model designed as a significant upgrade for understanding and precise spatia
arXiv:2604.01315v2 Announce Type: replace Abstract: Money launderers take advantage of limitations in existing detection approaches by hiding their financial footprints in a deceitful manner. They man
arXiv:2604.11867v1 Announce Type: cross Abstract: We set out to train behavioral dispositions (self-verification, uncertainty acknowledgment, feedback integration) into small language models (0.6B to
arXiv:2604.12659v1 Announce Type: cross Abstract: Vision-language models(VLMs) are increasingly applied to visual stock price forecasting, yet existing benchmarks inadequately evaluate their understan
Document OCR benchmarks are still an open problem Existing document OCR benchmarks are either too narrowly focused on a specific type (e.g. FinTabNet, ChartQA), or on documents that aren’t reflective
arXiv:2604.12896v1 Announce Type: new Abstract: Multimodal language models (MLLMs) are increasingly paired with vision tools (e.g., depth, flow, correspondence) to enhance visual reasoning. However, d
arXiv:2604.12778v1 Announce Type: cross Abstract: Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while sparing healthy tissue. With the growing adoption
arXiv:2604.12813v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown promising performance on video quality assessment (VQA) tasks. However, adapting them to new
arXiv:2604.12948v1 Announce Type: new Abstract: LLM agents with persistent memory store information as flat factual records, providing little context for temporal reasoning, change tracking, or cross-
arXiv:2603.07083v2 Announce Type: replace Abstract: Model-based reinforcement learning (MBRL) agents operating in high-dimensional observation spaces, such as Dreamer, rely on learning abstract repres
arXiv:2603.22607v2 Announce Type: replace Abstract: Recent advances in Virtual Try-On (VTON) and Virtual Try-Off (VTOFF) have greatly improved photo-realistic fashion synthesis and garment reconstruct
arXiv:2604.12403v1 Announce Type: new Abstract: Test-Time Prompt Tuning (TPT) adapts vision-language models using augmented views, but its effectiveness is hindered by the challenge of determining whi
arXiv:2604.06063v2 Announce Type: replace Abstract: The advent of Text-to-Image generative models poses significant risks of copyright violation and deepfake generation. Since the rapid proliferation
arXiv:2604.12579v1 Announce Type: new Abstract: Electroencephalography (EEG)-based multimodal learning integrates brain signals with complementary modalities to improve mental state assessment, provid
arXiv:2604.12780v1 Announce Type: cross Abstract: Vision Transformer (ViT) models have achieved remarkable performance across various vision tasks, with scalability being a key advantage when applied
arXiv:2604.12320v1 Announce Type: cross Abstract: While video large language models (Video-LLMs) excel in understanding slow-paced, real-world egocentric videos, their capabilities in high-velocity, i
arXiv:2604.12592v1 Announce Type: new Abstract: This paper presents our approach to the NTIRE 2026 3D Restoration and Reconstruction Challenge (Track 1), which focuses on reconstructing high-quality 3
Emergent Labs Inc., a vibe coding platform for building production-ready software, today announced the launch of Wingman, a personal, autonomous artificial intelligence agent that helps people manage
arXiv:2604.12047v1 Announce Type: new Abstract: PDF files are primarily intended for human reading rather than automated processing. In addition, the heterogeneous content of PDFs, such as text, table
arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).
arXiv:2602.13851v3 Announce Type: replace-cross Abstract: Formal specifications are crucial for building verifiable and dependable software systems, yet generating accurate and verifiable specificatio
arXiv:2604.12176v1 Announce Type: new Abstract: Relational reasoning is the ability to infer relations that jointly bind multiple entities, attributes, or variables. This ability is central to scienti
arXiv:2604.12559v1 Announce Type: new Abstract: Unstructured model editing aims to update models with real-world text, yet existing methods often memorize text holistically without reliable fine-grain
arXiv:2510.25512v2 Announce Type: replace-cross Abstract: Deep networks have shown remarkable performance across a wide range of tasks, yet getting a global concept-level understanding of how they fun
arXiv:2604.11929v1 Announce Type: new Abstract: Our ability to predict, control, and ultimately understand complex systems rests on discovering the equations that govern their dynamics. Identifying th
arXiv:2603.01591v2 Announce Type: replace-cross Abstract: Training-free diffusion priors enable inverse-problem solvers without retraining, but for nonlinear forward operators data consistency often r
arXiv:2604.12656v1 Announce Type: cross Abstract: End-to-end diffusion planning has shown strong potential for autonomous driving, but the physical feasibility of generated trajectories remains insuff
arXiv:2604.11996v1 Announce Type: cross Abstract: Should we trust Large Language Models (LLMs) with high accuracy? LLMs achieve high accuracy on reasoning benchmarks, but correctness alone does not re
arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional
arXiv:2604.11922v1 Announce Type: cross Abstract: Using FlowBoost, a closed-loop deep generative optimization framework for extremal structure discovery, we investigate ell^p-generalizations of the fi
arXiv:2506.14092v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in decision-support systems for high-stakes domains such as hiring and university admissions,
arXiv:2604.12666v1 Announce Type: cross Abstract: Text-based web agents offer computational efficiency for autonomous web navigation, yet developing robust agents remains challenging due to the noisy
arXiv:2604.12147v1 Announce Type: cross Abstract: Agents aspire to eliminate the need for task-specific prompt crafting through autonomous reason-act-observe loops. Still, they are commonly instructed
arXiv:2604.12290v1 Announce Type: new Abstract: Current LLM agent benchmarks, which predominantly focus on binary pass/fail tasks such as code generation or search-based question answering, often negl
arXiv:2604.12344v1 Announce Type: cross Abstract: The exponential growth of data from modern radio telescopes presents a significant challenge to traditional single-pulse search algorithms, which are
arXiv:2604.12168v1 Announce Type: cross Abstract: The applications of Generative Artificial Intelligence (GenAI) and their intersections with data-driven fields, such as healthcare, finance, transport
arXiv:2604.12351v1 Announce Type: new Abstract: Automated diagnosis based on color fundus photography is essential for large-scale glaucoma screening. However, existing deep learning models are typica
arXiv:2604.12306v1 Announce Type: cross Abstract: Climate decision-making in the Gulf increasingly demands systems that can translate heterogeneous scientific and policy evidence into actionable guida
arXiv:2604.12336v1 Announce Type: cross Abstract: Streaming Data-Driven Optimization (SDDO) problems arise in many applications where data arrive continuously and the optimization environment evolves
Gemini 3.1 Flash TTS Google released Gemini 3.1 Flash TTS today, a new text-to-speech model that can be directed using prompts. It's presented via the standard Gemini API using gemini-3.1-flash-tts-pr
Gemini 3.1 Flash TTS is rolling out in Google Vids and is available today in preview via the Gemini API and in @GoogleAIStudio. Whether you’re creating a pitch deck or recording a passion project, tra
Google DeepMind's Gemini 3.1 Flash TTS is a text-to-speech model delivering improved controllability, expressivity, and quality for developers, enterprises, and everyday users building AI-speech appli
arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece
arXiv:2604.13030v1 Announce Type: new Abstract: While diffusion models dominate the field of visual generation, they are computationally inefficient, applying a uniform computational effort regardless
arXiv:2604.12757v1 Announce Type: cross Abstract: Adversarial robustness is essential for deploying neural networks in safety-critical applications, yet standard evaluation methods either require expe
arXiv:2507.01770v4 Announce Type: replace-cross Abstract: This paper introduces a numerical method to enclose the global minimum of a nonlinear function subject to simple bounds on the variables. Usin
arXiv:2604.12978v1 Announce Type: new Abstract: Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cl
arXiv:2604.11924v1 Announce Type: new Abstract: While LLMs hold significant potential to transform scientific research, we advocate for their use to augment and empower researchers rather than to auto
Google LLC is enhancing the version of its Gemini assistant that is embedded in Chrome with a new time-saving tool called Skills. The capability started rolling out today. It’s accessible on Mac, Wind