Knowledge catalogue
arXiv:2605.02764v1 Announce Type: new Abstract: We present FoR-Net, a lightweight architecture for semantic segmentation that focuses on identifying and enhancing hard regions. Instead of relying on h
For those affected, you're going to see a lot of advice on social media for what to do next. I like Claire's tweet a lot. Here's my version of her tweet for millennial/gen x business professionals: -
arXiv:2605.00836v1 Announce Type: new Abstract: Sampling from Flow Matching generative models requires solving an ordinary differential equation (ODE) whose computational cost is dominated by neural n
arXiv:2605.02130v1 Announce Type: new Abstract: Human-level agentic intelligence extends beyond low-level geometric perception, evolving from recognizing where things are to understanding what they ar
arXiv:2605.01495v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by grounding responses in external knowledge during inference. However, conve
arXiv:2509.24276v4 Announce Type: replace Abstract: Large language models (LLMs) excel at complex reasoning but remain limited by static and incomplete parametric knowledge. Retrieval-augmented genera
arXiv:2605.01272v1 Announce Type: new Abstract: The development of video game streaming has grown rapidly, with major platforms such as YouTube and Twitch using different codecs. To support quality as
arXiv:2605.00371v1 Announce Type: cross Abstract: In this paper, we propose GaMMA, a state-of-the-art (SoTA) large multimodal model (LMM) designed to achieve comprehensive musical content understandin
arXiv:2601.22709v3 Announce Type: replace Abstract: Vision-Language Models (VLMs) achieve strong multimodal performance but are costly to deploy, and post-training quantization often causes significan
arXiv:2605.00876v1 Announce Type: cross Abstract: Vision-language models (VLMs) read an image and produce text in a single forward pass, whereas radiologists typically inspect an image several times a
arXiv:2510.27359v2 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning (PEFT) has emerged as a key strategy for adapting large-scale pre-trained models to downstream tasks, but existing a
arXiv:2603.28767v2 Announce Type: replace Abstract: Recent image generation models have shown strong capabilities in generating high-fidelity and photorealistic images. However, they are fundamentally
arXiv:2605.00782v1 Announce Type: cross Abstract: Reliable spatial analysis in GIScience requires preserving coordinate semantics, topology, units, and geographic plausibility. Current LLM-based GIS s
arXiv:2605.01650v1 Announce Type: new Abstract: Reliable subnational population estimates are essential for applications, yet remain difficult where censuses are sparse, outdated or spatially coarse.
Google Home's May 2026 update brings a faster camera experience, Gemini 3.1 for complex voice commands, and new web-based controls. The refreshed camera UI features faster navigation and zoomed-in pre
Google Home users can now ask Gemini to complete more complex, multi-step tasks and combine multiple tasks in a single command. Google has updated Gemini for Home to Gemini 3.1, which it says will imp
Google DeepMind, Microsoft, and Elon Musk's xAI have agreed to allow the US government to review new AI models before they're released to the public. In an announcement on Tuesday, the Commerce Depart
As artificial intelligence moves from experimentation into production, government agencies are becoming an unexpected proving ground for large-scale workforce transformation. Faced with mounting opera
GPT-5.5 Instant is rolling out over the next two days as the default model to all ChatGPT users, and as ‘gpt-5.5-chat-latest’ in the API. Personalization improvements are rolling out to Plus and Pro u
OpenAI is rolling out GPT-5.5 Instant to all ChatGPT users as the new default model, replacing GPT-5.3 Instant . The model produces 52.5% fewer hallucinated claims than its predecessor on high-stakes
GPT-5.5 Instant is starting to roll out in ChatGPT. It’s a big upgrade, giving you smarter, clearer, and more personalized answers in a warmer, more natural tone. And it's also more concise, which we
GPT-5.5 Instant is OpenAI's faster, more efficient variant of their GPT-5.5 model, designed to deliver improved reasoning and clarity while maintaining lower latency for real-time applications. The mo
GPT-5.5 Instant is a faster, more efficient variant of OpenAI's GPT-5.5 model designed for real-time applications and lower-latency tasks. The system card documents the model's capabilities, limitatio
arXiv:2605.01203v1 Announce Type: cross Abstract: Currently, process reward models (PRMs) have exhibited remarkable potential for test-time scaling. Since large language models (LLMs) regularly genera
arXiv:2604.03190v2 Announce Type: replace Abstract: Transformer attention computes a single softmax-weighted average over values -- a one-pass estimate that cannot correct its own errors. We introduce
arXiv:2409.14500v5 Announce Type: replace Abstract: Although data that can be naturally represented as graphs is widespread in real-world applications across diverse industries, popular graph ML bench
arXiv:2603.09625v2 Announce Type: replace Abstract: Deep learning models benefit from increasing data diversity and volume, motivating synthetic data augmentation to improve existing datasets. However
arXiv:2507.07129v3 Announce Type: replace-cross Abstract: We study a constrained training regime for decoder-only Transformers in which the token interface is fixed, previously trained dense blocks ar
arXiv:2605.02443v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities across diverse natural language processing tasks, yet they remain susceptible to
arXiv:2605.02596v1 Announce Type: new Abstract: With each sensing modality exhibiting inherent strengths and limitations, multi-modal approaches for wearable Human Activity Recognition (HAR) are becom
// HeavySkill // One of the cleaner takes on agentic harness design I've read. They argue that what actually drives agent harness performance is not the orchestration code. It's a single inner skill:
arXiv:2604.05134v2 Announce Type: replace Abstract: We study how reasoning evolves in a language model -- from supervised fine-tuning (SFT) to reinforcement learning (RL) -- by analyzing how a set of
arXiv:2605.00865v1 Announce Type: cross Abstract: EEG based phoneme decoding is promising for brain computer interfaces, but many prior studies rely on within subject evaluation, small cohorts, or wea
arXiv:2502.16435v4 Announce Type: replace-cross Abstract: Humans develop perception through a bottom-up hierarchy: from basic primitives and Gestalt principles to high-level semantics. In contrast, cu
This post documents a user's experiment comparing ChatGPT and Gemini's ability to create perspective portrait artwork using two reference images (a front-facing photo and a profile photo) along with a
I detected a bad Agent action, what do I do about it? this is pretty much the main question that will power the future’s Human+Agent driven improvement loops Gather data -> Mine Errors -> Find out whi
i have yet to meet a single person who feels like claude code is getting exponentially better on some kind of fast take off Anthropic pays $750K/ year per senior engineer. The creator of Claude Code j
arXiv:2601.17723v2 Announce Type: replace Abstract: Implicit neural representation (INR) has become the standard approach for arbitrary-scale image super-resolution (ASSR). To date, no empirical study
arXiv:2605.01627v1 Announce Type: new Abstract: Low-rank decomposition is a compelling approach for compressing large language models, but its effectiveness hinges on selecting which singular-vector b
“Indispensable reading” If you aren’t reading my newsletter, you probably should be! Today’s dispatch is on the Dawkins Debacle and cites @GaryMarcus, who has been indispensable reading over the last
arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i
arXiv:2605.00572v1 Announce Type: new Abstract: Algorithm performance in combinatorial optimization is highly sensitive to parameter settings, while a single globally tuned configuration often fails t
arXiv:2512.21788v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning of Diffusion Transformers (DiTs) for diverse, multi-conditional tasks often suffers from task interference when usin
arXiv:2605.01409v1 Announce Type: cross Abstract: The growing availability of health-related instructional videos creates new opportunities for clinical training, patient rehabilitation, and health ed
arXiv:2605.01036v1 Announce Type: new Abstract: This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physicall
arXiv:2605.00940v1 Announce Type: new Abstract: A new interpretable experiential learning model based on state history and global feedback is presented. It is capable of learning a behavioral model re
Managing agents and their actions can quickly grow in complexity and introduce security risks unique to AI. To address these challenges, at Google Cloud Next we announced Agent Gateway to provide simp
arXiv:2602.07238v2 Announce Type: replace-cross Abstract: Do leading LLM developers possess a proprietary ``secret sauce'', or is LLM performance driven by scaling up compute? Using training and bench
arXiv:2512.04032v3 Announce Type: replace Abstract: We present jina-vlm, a token-efficient 2.4B parameter vision-language model that achieves state-of-the-art multilingual VQA performance among open 2
arXiv:2605.01742v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved strong performance in visual recognition, yet their deployment in resource-constrained industrial environments
arXiv:2605.02288v1 Announce Type: new Abstract: Automated laboratories hold the promise of accelerating scientific discovery, yet their deployment is bottlenecked by the difficulty of designing safe a
arXiv:2604.17465v2 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a certain degree, verbalize the difference between perturbations applied to th
This newsletter episode covers recent AI industry developments including a legal dispute between OpenAI and Elon Musk, Microsoft's involvement in AI developments, the release of DeepSeek's v4 model, a
arXiv:2505.20340v3 Announce Type: replace Abstract: Understanding how latent representations evolve during generation is a central open problem in large language model interpretability. We introduce e
arXiv:2605.00899v1 Announce Type: new Abstract: We present LatentDiff, a scalable framework for semantic dataset comparison that operates directly in the latent space of pretrained vision encoders. By
arXiv:2605.01046v1 Announce Type: new Abstract: LoRA adapts large language models (LLMs) by restricting updates to low-rank subspaces of pre-trained weights. While this substantially reduces training
arXiv:2605.00913v1 Announce Type: new Abstract: Sensor-based Human Activity Recognition (HAR) has attracted increasing attention in medical and healthcare monitoring, particularly with the growth of I
arXiv:2605.01711v1 Announce Type: new Abstract: Existing research largely attributes the global sequence modeling capability of Transformers to the explicit computation of attention weights, a process
arXiv:2605.00884v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong semantic grounding and task generalization in manipulation, but aerial deployment remains difficul
arXiv:2603.00042v2 Announce Type: replace Abstract: We identify the Spectral Energy Gain in extreme model compression, where low-rank binary approximations outperform tiny-rank floating-point baseline