Knowledge catalogue
arXiv:2601.23143v2 Announce Type: replace Abstract: Large reasoning models (LRMs) achieve remarkable performance by leveraging reinforcement learning (RL) on reasoning tasks to generate long chain-of-
arXiv:2510.01290v2 Announce Type: replace Abstract: The long-output context generation of large reasoning models enables extended chain of thought (CoT) but also drives rapid growth of the key-value (
Thinky's secret plan: 1: Increase Human<->AI bandwidth 2: Raise ceiling of human+AI intelligence 3: Help humans continue as main-characters in the new world We are at Step 1. Interaction Models are gr
This post describes an AI system that monitors its own codebase to identify missing monitoring points and automatically generates pull requests to fix detected bugs, demonstrating autonomous self-impr
This is a tutorial on diffusion and flow matching, based on my previous postings here. I’ve made available the PDF, a python notebook for people to play with it, and the TEX source so hopefully one of
This is going to get even worse as people realize that careful tuning in their prompts can make AI writing seem not like AI writing to readers. We expect word counts to align, in some way, with thinki
This is harder to build than it looks. Preserving full conversational context while swapping underlying model providers mid-flight is a surprisingly deep systems problem. Most tools drop state or forc
Gary Marcus critiques the typical hype cycle pattern where emerging technologies experience inflated expectations followed by inevitable disappointment. The post likely illustrates this cycle using a
This seems like a critical reason to open up about AI use in academia. Scholars are using old AI models, badly, and not talking about it. New models hallucinate very few citations, and good agentic ha
This works really well btw, at the end of your query ask your LLM to 'structure your response as HTML', then view the generated file in your browser. I've also had some success asking the LLM to prese
GitLab Act 2 There's a lot going on in this announcement from GitLab about the 'workforce reduction' and 'structural and strategic decisions' they are making with respect to the agentic era. They're '
arXiv:2605.07199v1 Announce Type: new Abstract: Marketing decisions reflect the interaction of latent consumer heterogeneity, time-varying internal states, and explicit interventions, a structure that
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. A few months before he was awarded the Nobel Prize in economic
arXiv:2605.07955v1 Announce Type: cross Abstract: Multiple sclerosis (MS) expresses substantial clinical and radiological heterogeneity, which poses significant challenges for automatic lesion segment
To be clear, I meant 'idea' in the context of science and engineering, in particular AI, as in 'theory' or 'invention', like a new theory of cognition or an idea for a new ML approach. I thought that
To train better open models, we need predictable scaling. Delphi is Marin’s first step: we pretrained many small models with one recipe, then extrapolated 300× to predict a 25B-param / 600B-token run
Today, we're announcing $30M in new funding to build the AI OS for Research. 2.5M researchers start their work with Consensus every month. Their work is the foundation that all progress is built upon.
Today we’re launching the OpenAI Deployment Company to help businesses build and deploy AI. It's majority-owned and controlled by OpenAI. It brings together 19 leading investment firms, consultancies,
Today we're sharing our work on interaction models. A new class of model trained from scratch to handle real-time interaction natively, instead of gluing it onto a turn-based one. https://youtu.be/A12
arXiv:2605.06683v1 Announce Type: cross Abstract: Transformer-based large language models are in some respects limited by the quadratic time and space computational complexity of attention. We introdu
arXiv:2605.07990v1 Announce Type: cross Abstract: When a tool-calling agent picks the wrong tool, the failure is invisible until execution: the email gets sent, the meeting gets missed. Probing 12 ins
arXiv:2605.07339v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in orchestrating tools for reasoning tasks. However, existing methods rely on a s
arXiv:2605.07158v1 Announce Type: cross Abstract: Vector search and retrieval-augmented generation (RAG) rest on the assumption that cosine similarity between text embeddings reflects conceptual relat
arXiv:2605.07172v1 Announce Type: new Abstract: Alignment of large language models (LLMs) via SFT and RLHF/DPO typically ignores the global geometry of the representation space, relying instead on loc
arXiv:2602.02739v2 Announce Type: replace-cross Abstract: Geometric data pruning methods, while practical for leveraging pretrained models, are fundamentally unstable. Their reliance on extrinsic geom
This post from AI researcher Gary Marcus likely discusses the enormous economic value or potential return on investment related to artificial intelligence developments, suggesting AI's worth or impact
arXiv:2605.07693v1 Announce Type: new Abstract: Geometric representation-conditioned molecule generation provides an effective paradigm that decouples molecule representation modeling from structure g
arXiv:2605.07799v1 Announce Type: cross Abstract: Training foundation models is computationally intensive and often slow to converge.We introduce PIQL,Privileged Information for Quick and Quality Lear
arXiv:2605.05368v2 Announce Type: replace-cross Abstract: Information is one of the most widely-discussed concepts of the current era. However, a great deal of insightful work notwithstanding, it is y
arXiv:2605.07986v1 Announce Type: cross Abstract: AI measurement science has a wide variety of methodologies and measurements for comparing AI systems, resulting in what often appear to be 'apples-to-
arXiv:2605.07202v1 Announce Type: new Abstract: Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limi
arXiv:2605.07655v1 Announce Type: cross Abstract: Searching a multi-biometric database of a billion records for a country-level identity system requires pushing the limits of all aspects of a biometri
arXiv:2605.07013v1 Announce Type: new Abstract: Diffusion language models (DLMs) promise parallel, order-agnostic generation, but on standard benchmarks they have historically lagged behind autoregres
arXiv:2605.07049v1 Announce Type: cross Abstract: We present the first theoretical guarantees for differentially private online reinforcement learning (RL) with general function approximation, extendi
arXiv:2602.09850v2 Announce Type: replace Abstract: Industrial anomaly detection demands precise reasoning over fine-grained defect patterns. However, existing multimodal large language models (MLLMs)
arXiv:2605.06891v1 Announce Type: new Abstract: Labeled datasets reflect the biases of their annotation pipelines, which sometimes introduce label bias: group-conditional label errors that cause syste
arXiv:2605.08054v1 Announce Type: new Abstract: Generating human motion that satisfies customized zero-shot goal functions, enabling applications such as controllable character animation and behavior
arXiv:2605.07232v1 Announce Type: new Abstract: Recent advances in generative AI have democratized video creation at scale. AI-generated videos, including partially manipulated clips across visual and
arXiv:2605.07429v1 Announce Type: new Abstract: Existing mobile devices are constrained by compact optical designs, such as small apertures, which make it difficult to produce natural, optically reali
arXiv:2605.06812v1 Announce Type: new Abstract: LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and mult
arXiv:2605.07677v1 Announce Type: cross Abstract: Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once
arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict
arXiv:2605.07593v1 Announce Type: new Abstract: Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams,
arXiv:2605.07935v1 Announce Type: new Abstract: We present TraceFix, a verification-first pipeline for Large Language Model (LLM) multi-agent coordination. An agent synthesizes a protocol topology as
arXiv:2605.07568v1 Announce Type: cross Abstract: The Arrow-of-Time (AoT) task, determining whether a video plays forward or backward by recognizing temporal irreversibility, is one humans solve with
arXiv:2605.07776v1 Announce Type: cross Abstract: Language model (LM) 'reasoning', commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics u
arXiv:2605.07412v1 Announce Type: cross Abstract: Although Global Navigation Satellite Systems (GNSS) provide a general solution for bike tracking outdoors, there still exist complex riding environmen
arXiv:2605.06966v1 Announce Type: new Abstract: Autonomous vehicles (AVs) require extensive testing in simulation, but test case generation for driving scenarios is laborious. The desired scenarios ar
arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia
arXiv:2605.07772v1 Announce Type: new Abstract: Transformers perform inference by iteratively transforming token representations across layers. This layerwise computation has been studied empirically,
arXiv:2605.07924v1 Announce Type: cross Abstract: Discrete flow matching generates text by iteratively transforming noise tokens into coherent language, but may require hundreds of forward passes. Dis
arXiv:2605.06990v1 Announce Type: new Abstract: Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL
arXiv:2605.07471v1 Announce Type: new Abstract: Machine-learning models in high-energy physics are often trained on simulated data, where fully simulated samples are computationally expensive while fa
arXiv:2605.06726v1 Announce Type: new Abstract: Inferring the identity of wildlife species from daily movement data alone is a challenging task. We train sequence models on large-scale, 7-species GPS
arXiv:2605.08025v1 Announce Type: new Abstract: Tree ring marking remains a key step in dendrometry and dendrochronology, but it is often performed manually, making the process time-consuming, subject
arXiv:2605.06906v1 Announce Type: new Abstract: Human mobility differs from text and from generic time series in three structural ways: visits are tuple-valued events whose meaning depends on the join
arXiv:2605.07922v1 Announce Type: new Abstract: Learning hierarchical features in Sparse Autoencoders (SAEs) is essential for capturing the structured nature of real-world data and mitigating issues l
arXiv:2605.06889v1 Announce Type: new Abstract: Pairwise translation directions are a key input to camera location estimation in global structure-from-motion. Existing estimators usually process each
arXiv:2605.07143v1 Announce Type: new Abstract: Translation averaging aims to recover camera locations from pairwise relative translation directions and is a fundamental component of global Structure-
Tripo 3.1 is now supported in ComfyUI via Partner Nodes. Generate high-detail 3D assets directly in your existing ComfyUI workflows, with denser geometry and cleaner surfaces for close-up production.