Knowledge catalogue
Sebastian Raschka has updated his LLM architecture gallery with higher resolution figures and improved summaries, including coverage of the DeepSeek V4 model architecture. This resource provides visua
Qwen's latest model improvements focus on achieving more consistent and uniform performance quality across different artistic styles and aesthetic domains, reducing the variability in output quality t
Since GPT-5.4, we’ve unified Codex and the main model into a single system, so there’s no separate coding line anymore. GPT-5.5 takes this further, with strong gains in agentic coding, computer use, a
arXiv:2505.09971v3 Announce Type: replace Abstract: Airborne laser scanning (ALS) point cloud semantic segmentation is a fundamental task for large-scale 3D scene understanding. Fixed models deployed
arXiv:2601.11194v2 Announce Type: replace Abstract: We suggest a new multi-modal algorithm for joint inference of paired structurally aligned samples with Rectified Flow models. While some existing me
arXiv:2604.21724v1 Announce Type: new Abstract: Large token-indexed lookup tables provide a compute-decoupled scaling path, but their practical gains are often limited by poor parameter efficiency and
arXiv:2604.21260v1 Announce Type: cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be mi
arXiv:2506.21546v4 Announce Type: replace-cross Abstract: Segmentation Vision-Language Models (VLMs) have significantly advanced grounded visual understanding, yet they remain prone to pixel-grounding
arXiv:2604.21469v1 Announce Type: new Abstract: Automating the detection of regulatory compliance remains a challenging task due to the complexity and variability of legal texts. Models trained on one
arXiv:2604.21428v1 Announce Type: new Abstract: Modern large-scale language model pre-training relies heavily on the single program multiple data (SPMD) paradigm, which requires tight coupling across
DeepSeek-V4-Pro is a Mixture-of-Experts language model with 1.6 trillion total parameters and 49 billion activated per token, supporting a 1 million token context length. Released under the MIT Licens
Raphael Satter / Reuters: Diplomatic cable: US State Department has ordered a global push to bring attention to what it says are efforts by Chinese companies to steal IP from US AI labs — The U.S. Sta
arXiv:2601.13690v2 Announce Type: replace Abstract: Clinical Decision Support Systems (CDSSs) provide reasoning and inquiry guidance for physicians, yet they face notable challenges, including high ma
arXiv:2604.21473v1 Announce Type: cross Abstract: In the treatment of complex diseases, treatment regimens using a single drug often yield limited efficacy and can lead to drug resistance. In contrast
arXiv:2604.21070v1 Announce Type: new Abstract: Summarizing long, domain-specific documents with large language models (LLMs) remains challenging due to context limitations, information loss, and hall
arXiv:2604.21694v1 Announce Type: cross Abstract: Video copy detection requires robust similarity estimation under diverse visual distortions while operating at very large scale. Although deep neural
arXiv:2604.21668v1 Announce Type: new Abstract: The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion
arXiv:2604.21229v1 Announce Type: cross Abstract: Large language model assistants are increasingly expected to retain and reason over information accumulated across many sessions. We introduce Engrama
arXiv:2512.05591v2 Announce Type: replace-cross Abstract: Large language model post-training relies on reinforcement learning to improve model capability and alignment quality. However, the off-policy
arXiv:2510.18914v4 Announce Type: replace-cross Abstract: Large language models often display undesirable behaviors embedded in their internal representations, undermining fairness, inconsistency drif
arXiv:2506.19579v3 Announce Type: replace-cross Abstract: Robotic scene understanding increasingly relies on Vision-Language Models (VLMs) to generate natural language descriptions of the environment.
arXiv:2509.21976v3 Announce Type: replace-cross Abstract: Referring expression understanding in remote sensing poses unique challenges, as it requires reasoning over complex object-context relationshi
arXiv:2604.21873v1 Announce Type: new Abstract: Physical video understanding requires more than naming an event correctly. A model can answer a question about pouring, sliding, or collision from textu
arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph em
arXiv:2604.14709v2 Announce Type: replace Abstract: Existing benchmarks for hardware design primarily evaluate Large Language Models (LLMs) on isolated, component-level tasks such as generating HDL mo
This post expresses hope that upgrading to DeepSeek v4 (an AI model) will improve the quality of bot-generated comments on a platform or service. The statement implies current bot comments are conside
arXiv:2604.21252v1 Announce Type: new Abstract: The LASSO-Clip-EN (LCEN) algorithm was previously introduced for nonlinear, interpretable feature selection and machine learning. However, its design an
arXiv:2505.20243v4 Announce Type: replace Abstract: Time plays a critical role in how information is generated, retrieved, and interpreted. In this survey, we provide a comprehensive overview of Tempo
arXiv:2604.21362v1 Announce Type: new Abstract: Creative Generation (CG) leverages generative models to automatically produce advertising content that highlights product features, and it has been a si
arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl
arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or
arXiv:2604.21870v1 Announce Type: cross Abstract: STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capaci
arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1
arXiv:2604.20848v1 Announce Type: cross Abstract: Large Language Model (LLM)-based recommendation systems have demonstrated remarkable capabilities in understanding user preferences and generating per
arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili
arXiv:2602.01493v2 Announce Type: replace-cross Abstract: Solving diverse partial differential equations (PDEs) is fundamental in science and engineering. Large language models (LLMs) have demonstrate
arXiv:2603.27112v2 Announce Type: replace Abstract: As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and de
arXiv:2604.21160v1 Announce Type: new Abstract: Point-Vision-Language Models promise to empower embodied agents with executable spatial reasoning, yet they frequently succumb to geometric hallucinatio
arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between
arXiv:2604.20851v1 Announce Type: cross Abstract: Modern video-text retrieval (VTR) models excel on in-distribution benchmarks but are highly vulnerable to real-world query shifts, where the distribut
arXiv:2510.26615v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external knowledge, but it must balance limited effective context, re
Fireworks AI announced the release or deployment of DeepSeek V4, a large language model, alongside another project or update called 'Spud' on the same day, with the team planning to work through the n
arXiv:2604.21346v1 Announce Type: new Abstract: Vision--language models (VLMs) often fail on abstract visual reasoning benchmarks such as Bongard problems, raising the question of whether the main bot
arXiv:2604.21330v1 Announce Type: new Abstract: Recent progress in deep learning has been driven by increasingly large-scale models, but the resulting computational cost has become a critical bottlene
arXiv:2604.20917v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of
arXiv:2511.18539v2 Announce Type: replace-cross Abstract: We propose TimePre, a simple framework that unifies the efficiency of Multilayer Perceptron (MLP)-based models with the distributional flexibi
arXiv:2604.20925v1 Announce Type: new Abstract: While current deep learning models achieve high performance by learning statistical correlations from vast datasets,which stands in stark contrast to hu
arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi
arXiv:2411.16771v3 Announce Type: replace Abstract: Vision Large Language Models (VLLMs) are widely acknowledged to be prone to hallucinations. Existing research addressing this problem has primarily
arXiv:2604.21082v1 Announce Type: new Abstract: Training vision-language models (VLMs) for medical report generation is often hindered by the scarcity of high-quality annotated data. This work evaluat
GPT-5.5 is out. It's available in OpenAI Codex and is rolling out to paid ChatGPT subscribers. I've had some preview access and found it to be a fast, effective and highly capable model. As is usually
arXiv:2604.20273v1 Announce Type: new Abstract: We present ActuBench, a multi-agent LLM pipeline for the automated generation and evaluation of advanced actuarial assessment items aligned with the Int
Always enjoy getting to chat with @swyx on our annual cross-episode with @latentspacepod on the state of AI. We hit on what’s shifted, what surprised us and what’s next. We covered: ▪️ Whether AI infr
arXiv:2604.20732v1 Announce Type: cross Abstract: Freight brokerages negotiate thousands of carrier rates daily under dynamic pricing conditions where models frequently revise targets mid-conversation
Anthropic's tightly controlled rollout of Claude Mythos has taken an awkward turn. After spending weeks insisting the AI model is so capable at cybersecurity that it is too dangerous to release public
arXiv:2604.20267v1 Announce Type: cross Abstract: Audio carries richer information than text, including emotion, speaker traits, and environmental context, while also enabling lower-latency processing
arXiv:2601.02896v2 Announce Type: replace Abstract: Controlling emergent behavioral personas (e.g., sycophancy, hallucination) in Large Language Models (LLMs) is critical for AI safety, yet remains a
arXiv:2604.19954v1 Announce Type: new Abstract: Current text-to-image models struggle to provide precise camera control using natural language alone. In this work, we present a framework for precise c
arXiv:2602.20181v2 Announce Type: replace-cross Abstract: Residential energy retrofit initiation is often stalled by an expertise gap, where homeowners lack the technical literacy required for structu
Claude users can access more apps with Anthropic's AI now thanks to new connectors for everything from hiking to grocery shopping. Anthropic already supported connecting numerous work-related apps to