Knowledge catalogue
Anthropic’s CEO keeps talking about AI wiping out jobs because he’s trying to IPO this year. If he positions Claude as armageddon for jobs, his TAM becomes “all white-collar human labor,” not just AI
GDPval is one of the most important benchmarks of AI ability because it is based on human expertise. It compares expert human performance to AI performance using expert human judges who spend an avera
NEW paper from Apple. Interesting idea: 'Attention to Mamba'. The paper introduces a two-stage recipe for cross-architecture distillation from Transformers into Mamba. Naive distillation collapses tea
Nice paper from Google. And a great application of AI agents. Wearables capture a staggering amount of physiological signals every day. CoDaS is an AI co-data-scientist that turns raw wearable sensor
This post likely expresses enthusiasm about Hermes, an AI model, comparing the experience of using it to a profound sensory revelation. The metaphor suggests that Hermes represents a significant quali
The quality of thinking acts as a multiplier on progress made during iterative work, but iteration frequency itself is the primary driver of success. This insight from AI researcher François Chollet e
This post documents a Wordle game result where the player solved puzzle #1,763 in 5 attempts, with the final answer being a five-letter word. The emoji grid shows the progression of guesses, indicatin
arXiv:2604.14902v1 Announce Type: cross Abstract: Intelligent embodied agents should not simply follow instructions, as real-world environments often involve unexpected conditions and exceptions. Howe
arXiv:2510.01433v2 Announce Type: replace Abstract: Vision-based robot learning often relies on dense image or point-cloud inputs, which are computationally heavy and entangle irrelevant background fe
arXiv:2604.14779v1 Announce Type: cross Abstract: In continual visual question answering (VQA), existing Continual Learning (CL) methods are mostly built for symmetric, unimodal architectures. However
This article from Latent Space discusses Anthropic's Claude Opus 4.7 release, highlighting incremental improvements across multiple performance dimensions compared to the previous 4.6 version. The pie
arXiv:2604.14179v1 Announce Type: new Abstract: Rare diseases affect over 300 million people worldwide and are characterized by complex care pathways, limited clinical expertise, and substantial unmet
arXiv:2508.15396v2 Announce Type: replace Abstract: The increasing adoption of large language models (LLMs) has raised serious concerns about their reliability and trustworthiness. As a result, a grow
arXiv:2512.22185v2 Announce Type: replace Abstract: Intracranial aneurysm rupture causes subarachnoid hemorrhage with mortality near 50%, making early detection critical. Although CTA enables rapid sc
arXiv:2604.13101v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into aviation safety decision-making represents a significant technological advancement, yet their sta
arXiv:2604.14251v1 Announce Type: new Abstract: Monitoring LLM safety at scale requires balancing cost and accuracy: a cheap latent-space probe can screen every input, but hard cases should be escalat
arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal
arXiv:2604.15224v1 Announce Type: cross Abstract: The extit{LLM-as-a-judge} paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: th
arXiv:2602.16716v3 Announce Type: replace Abstract: Contextuality is a central feature of quantum theory, traditionally understood as the impossibility of reproducing quantum measurement statistics us
arXiv:2604.13100v1 Announce Type: cross Abstract: The shift toward intent-driven software engineering (often termed 'Vibe Coding') exposes a critical Context-Fidelity Trade-off: vague user intents ove
arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre
arXiv:2604.14733v1 Announce Type: new Abstract: Regrasp planning is often required when one pick-and-place cannot transfer an object from an initial pose to a goal pose while maintaining grasp feasibi
arXiv:2511.22521v2 Announce Type: replace Abstract: Document visual question answering requires models not only to answer questions correctly, but also to precisely localize answers within complex doc
arXiv:2604.14572v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds LLM responses in external evidence but treats the model as a passive consumer of search results: it never
arXiv:2603.25903v2 Announce Type: replace Abstract: Scaling robot learning to long-horizon tasks remains a formidable challenge. While end-to-end policies often lack the structural priors needed for e
arXiv:2511.09149v4 Announce Type: replace Abstract: While natural language is the de facto communication medium for LLM-based agents, it presents a fundamental constraint. The process of downsampling
arXiv:2604.14267v1 Announce Type: new Abstract: Search agents extend Large Language Models (LLMs) beyond static parametric knowledge by enabling access to up-to-date and long-tail information unavaila
arXiv:2604.14306v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated high proficiency on English-centric medical examinations, their performance often declines when fac
arXiv:2604.14640v1 Announce Type: new Abstract: The proliferation of financial misinformation poses a severe threat to market stability and investor trust, misleading market behavior and creating crit
arXiv:2510.15946v3 Announce Type: replace Abstract: Internet memes have emerged as a popular multimodal medium, yet they are increasingly weaponized to convey harmful opinions through subtle rhetorica
arXiv:2604.06647v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems are typically evaluated under static assumptions, despite being frequently corrected through user or ex
arXiv:2510.14133v2 Announce Type: replace Abstract: Agentic AI systems, which leverage multiple autonomous agents and large language models (LLMs), are increasingly used to address complex, multi-step
arXiv:2604.15037v1 Announce Type: cross Abstract: Recent advancements in LLM agents are gradually shifting from reactive, text-based paradigms toward proactive, multimodal interaction. However, existi
arXiv:2604.13888v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into Geographic Information Systems (GIS) marks a paradigm shift toward autonomous spatial analysis. How
arXiv:2604.14302v1 Announce Type: new Abstract: We tackle a new problem: generating geometrically consistent multi-view scenes from a single freehand sketch. Freehand sketches are the most geometrical
Claude Opus 4.7 'thinks more' at higher effort levels, particularly on later turns in agentic settings. Anthropic introduced a new 'xhigh' (extra high) effort level between high and max to give users
arXiv:2604.14166v1 Announce Type: new Abstract: Mapping Cyber Threat Intelligence (CTI) text to MITRE ATT&CK technique IDs is a critical task for understanding adversary behaviors and automating threa
A guide on disabling thinking mode in Ollama models using the CLI by running models with the `--think=false` flag or using `/set nothink` followed by a prompt. The post likely discusses how to configu
I'll give Anthropic credit for moving quickly. Opus 4.7 Adaptive Thinking now triggers thinking much more often, including for the tasks it failed at yesterday. That also means it is doing a lot more
arXiv:2604.13203v1 Announce Type: cross Abstract: Mild Cognitive Impairment (MCI) affects 15-20% of adults aged 65 and older, often making kitchen navigation and independent living difficult, particul
This year's PyCon US is coming up next month from May 13th to May 19th, with the core conference talks from Friday 15th to Sunday 17th and tutorial and sprint days either side. It's in Long Beach, Cal
arXiv:2604.05158v2 Announce Type: replace Abstract: Large language models encode extensive world knowledge valuable for zero-shot named entity recognition. However, their causal attention mechanism, w
arXiv:2604.00313v2 Announce Type: replace Abstract: Automated species classification from underwater imagery is bottlenecked by the cost of expert annotation, and supervised models trained on one data
arXiv:2603.17512v4 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general intelligence, yet their multilingual performance remains highly imbalanced. Although LLMs encode
Last week, Anthropic announced Project Glasswing alongside Claude Mythos Preview, a model they described as so powerful at finding vulnerabilities they couldn't release it. The announcement featured A
arXiv:2501.11711v2 Announce Type: replace Abstract: The COVID-19 pandemic has claimed millions of lives, spurring the development of diverse forecasting models. In this context, the true utility of co
arXiv:2502.07408v2 Announce Type: replace-cross Abstract: Deep Neural Networks (DNNs) can be catastrophically disrupted by flipping only a handful of parameter bits. We introduce Deep Neural Lesion (D
arXiv:2604.14218v1 Announce Type: new Abstract: Hate speech detection in Devanagari-scripted social media memes presents compounded challenges: multimodal content structure, script-specific linguistic
arXiv:2509.23468v3 Announce Type: replace-cross Abstract: Effectively integrating diverse sensory modalities is crucial for robotic manipulation. However, the typical approach of feature concatenation
arXiv:2604.14199v1 Announce Type: cross Abstract: Predicting real-world events from live market signals demands systems that fuse qualitative news with quantitative order-book dynamics under strict te
arXiv:2604.03611v2 Announce Type: replace Abstract: Portrait composition plays a central role in portrait aesthetics and visual communication, yet existing datasets and benchmarks mainly focus on coar
arXiv:2604.15272v1 Announce Type: cross Abstract: This paper presents Prism, the first symbolic superoptimizer for tensor programs. The key idea is sGraph, a symbolic, hierarchical representation that
arXiv:2604.14885v1 Announce Type: new Abstract: Autoregressive decoding in Large Language Models (LLMs) generates one token per step, causing high inference latency. Speculative decoding (SD) mitigate
arXiv:2604.14862v1 Announce Type: new Abstract: Constrained decoding has been widely adopted for structured generation with large language models (LLMs), ensuring that outputs satisfy predefined forma
Sharing my current setup to run Qwen3.6 locally in a good agentic setup (Pi + llama.cpp). Should give you a good overview of how good local agents are today: # Start llama.cpp server: llama-server -hf
arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a
arXiv:2509.15602v5 Announce Type: replace Abstract: Multimodal large language models (MLLMs) excel at general video understanding but struggle with fast, high-frequency sports like tennis, where rally
To go deeper on our new Life Sciences model series, research lead @joyjiao12 and product lead Yunyun Wang joined @AndrewMayne on the OpenAI Podcast to discuss how we’re building models for biology, dr
arXiv:2604.14237v1 Announce Type: new Abstract: Transistor topology optimization is a critical step in standard cell design, directly dictating diffusion sharing efficiency and downstream routability.
arXiv:2604.14550v1 Announce Type: cross Abstract: Generating synthesizable Verilog for large, hierarchical hardware designs remains a significant challenge for large language models (LLMs), which stru