Knowledge catalogue
arXiv:2605.27896v1 Announce Type: new Abstract: Recently, large language models (LLMs) have achieved superior performance in static financial reasoning and simple dynamic trading tasks. However, exist
This article likely discusses the discovery and analysis of compiler bugs or miscompilation errors in software development tools, exploring how developers identify these issues and their implications
This post discusses how compiler bugs or miscompiles can be discovered and exploited without expensive AI systems, illustrating that significant computational costs can be incurred quickly when identi
arXiv:2605.27856v1 Announce Type: cross Abstract: Recommendation systems power engagement and monetization across feeds, ads, and short-video platforms, but translating the latest advances in Large La
arXiv:2605.27774v1 Announce Type: new Abstract: In-context learning -- performing tasks based on examples given in the prompt -- is an important capability that has emerged in large language models an
arXiv:2605.27452v1 Announce Type: new Abstract: Bridge inspection in Japan requires mandatory visual assessments every five years, yet qualitative damage ratings (levels a-e) assigned by different eng
arXiv:2603.02702v3 Announce Type: replace Abstract: The financial domain involves a variety of important time-series problems. Recently, time-series analysis methods that jointly leverage textual and
arXiv:2605.28501v1 Announce Type: new Abstract: Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-d
arXiv:2510.02174v3 Announce Type: replace Abstract: Flatness of the loss landscape has been widely studied as an important perspective for understanding the behavior and generalization of deep learnin
arXiv:2605.28174v1 Announce Type: cross Abstract: Foundation models offer a promising route to transferable remote sensing representations, but many current approaches depend on very large pretraining
arXiv:2605.21832v2 Announce Type: replace Abstract: Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates coll
Ryan Lawler / Axios: Fonoa, which helps enterprises manage indirect tax compliance, raised a 110M Series C led by Headline and acquired PwC's Indirect Tax Edge platform — Fonoa, which helps enterprise
NOAA forecasts a 55% chance of a below-normal 2026 Atlantic hurricane season (June 1 - November 30) with 8-14 named storms, 3-6 hurricanes, and 1-3 major hurricanes. The below-average forecast is driv
arXiv:2605.27590v1 Announce Type: new Abstract: Remote sensing question answering (RS-QA) often requires more than direct semantic prediction, especially in large-scale forest scenes where ecological
arXiv:2510.17620v2 Announce Type: replace Abstract: Large language models may encode sensitive information or outdated knowledge that needs to be removed, to ensure responsible and compliant model res
arXiv:2601.19302v3 Announce Type: replace Abstract: This paper introduces Formula Prompting (FP) and Formula-One Prompting (F-1), two single-call methods that elicit governing equations before solving
arXiv:2605.27849v1 Announce Type: cross Abstract: Despite rapid progress in LLM-based code generation, existing models are predominantly trained on imperative languages, leaving functional programming
arXiv:2605.28188v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes decision-making settings such as legal reasoning, where consistency under factuall
Elizabeth Howcroft / Reuters: France's market regulator warns crypto companies they could face blacklisting and lawsuits if they don't have MiCA licenses by the EU's June 30 deadline — France's top ma
arXiv:2605.27919v1 Announce Type: cross Abstract: Learning visuomotor policies via behavior cloning typically involves mimicking expert demonstrations collected by human operators. However, natural hu
arXiv:2605.27451v1 Announce Type: new Abstract: The 10th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop and Competition, held at CVPR 2026, continues to advance research on modelling, analy
arXiv:2605.27387v1 Announce Type: cross Abstract: Diffusion models promise efficient parallel text generation but rely on bidirectional attention, creating a structural mismatch with pre-trained Autor
arXiv:2603.20980v2 Announce Type: replace-cross Abstract: Time-varying causal models provide a powerful framework for studying dynamic scientific systems, yet most existing approaches assume that the
arXiv:2605.27861v1 Announce Type: cross Abstract: Predicting whether two drugs interact (binary detection) is a substantially dif- ferent task from predicting the mechanism type of that interaction (m
arXiv:2605.28303v1 Announce Type: new Abstract: While Knowledge Editing (KE) enables efficient updates, its dominant Static Fact Overwriting paradigm treats LLMs as discrete databases, forcibly inject
arXiv:2605.27384v1 Announce Type: cross Abstract: This position paper reflects empirical data collected during my PhD from a large-scale within-subjects study (N = 90). The study compared a highly hum
arXiv:2605.28176v1 Announce Type: new Abstract: Background and objective. Conventional Deep Learning (DL) approaches for Knee Osteoarthritis (KOA) grading rely on one-hot labels, which fail to capture
arXiv:2605.28359v1 Announce Type: new Abstract: Evaluating whether large language model (LLM) agents can profit in capital markets is increasingly framed as end-to-end trading: place an agent in a his
arXiv:2605.28483v1 Announce Type: new Abstract: Linking learning resources to a structured competency framework is key to enabling competency-based search and curriculum analytics in Learning Manageme
arXiv:2605.28371v1 Announce Type: new Abstract: Industrial Prognostics and Health Management (PHM) provides a representative case study for a broader challenge in applied machine learning: translating
arXiv:2603.13003v2 Announce Type: replace Abstract: Cyber-physical robotic systems are vulnerable to false data injection attacks (FDIAs), in which an adversary corrupts sensor signals while evading r
arXiv:2605.28820v1 Announce Type: new Abstract: Current vision-language models (VLMs) typically stitch together separate image encoders and language decoders via multi-stage alignment, a modular frame
arXiv:2605.27944v1 Announce Type: new Abstract: With rapid advances in audio-visual generative models, reliable forgery detection becomes increasingly critical. Existing methods for audio-visual deepf
Fun fact: Australia is basically Scandinavia with the Sahara Desert bolted on. I LOVE this visualisation. Everyone imagines nature and the outback, but they don't realise just how urbanised we are. Cr
Gary Marcus shares a discussion thread about consciousness with user @Grimezsz on X (formerly Twitter), likely exploring philosophical, scientific, or technical perspectives on consciousness and relat
arXiv:2605.28500v1 Announce Type: cross Abstract: Large language models have shown impressive capabilities in code generation, yet they often produce functionally incorrect code. Uncertainty quantific
arXiv:2605.27864v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied in finance, yet most existing work emphasizes trading signals or financial NLP tasks centered on p
arXiv:2605.28816v1 Announce Type: new Abstract: World models for interactive video generation have largely focused on single-agent settings, where future observations are generated from a single contr
arXiv:2605.27491v1 Announce Type: new Abstract: We introduce GE-Sim 2.0 (Genie Envisioner World Simulator 2.0), a closed-loop video world simulator for robotic manipulation. Building on the action-con
arXiv:2605.28548v1 Announce Type: new Abstract: Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Acti
arXiv:2405.09689v2 Announce Type: replace-cross Abstract: Hyperdimensional Computing (HDC) is a computationally and data-efficient paradigm that acts as a bridge between connectionist and symbolic app
arXiv:2605.27934v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards improves language model reasoning, but its reliance on domain-specific verifiers, sparse outcome rewards,
arXiv:2605.27411v1 Announce Type: cross Abstract: Aim/Introduction: Distance-encoding biomorphic-informational neural network (DEBI-NN) is a recently proposed architecture in which connection weights
arXiv:2605.27499v1 Announce Type: new Abstract: Flow and diffusion generative models have established themselves as widely adopted density estimators for simulation-based inference (SBI), extending na
arXiv:2605.27990v1 Announce Type: cross Abstract: Diffusion posterior sampling conditions diffusion priors on measurements, but data-consistency updates are typically scaled by hand-tuned guidance wei
arXiv:2605.28200v1 Announce Type: new Abstract: Single-cell RNA sequencing (scRNA-seq) profiles large numbers of cells but loses spatial context, whereas spatial transcriptomics (ST) preserves partial
arXiv:2605.27970v1 Announce Type: new Abstract: While large language models (LLMs) are trained purely on textual data, prior work has shown that their internal representations can exhibit rich geometr
arXiv:2605.28233v1 Announce Type: cross Abstract: Fairness-accuracy trade-offs are a central concern in the deployment of fairness-aware machine learning methods. When sensitive attributes are unavail
glad to know Mythos' safety concerns have been addressed right as Anthropic also secured tens of billions in inference compute 👍 JUST IN: Anthropic announces it will roll out Claude Mythos “in the com
arXiv:2605.28273v1 Announce Type: new Abstract: The Policy-Space Response Oracles (PSRO) framework scales equilibrium computation to large zero-sum games by iteratively expanding a restricted strategy
Managing planned maintenance is a critical part of running a reliable business. But as your cloud footprint grows into hundreds or even thousands of projects, keeping track of every individual update
arXiv:2605.28454v1 Announce Type: new Abstract: Greedy Best-First Search (GBFS) is the dominant approach for solving search problems where the goal can be estimated with a heuristic, such as planning,
Good value for money We gave Grok Build 0.1 one prompt: build a webhook delivery service in TypeScript, Bun, and SQLite. It planned it, built it, and shipped a working demo. Total cost: $1.65. Zero to
arXiv:2408.00057v3 Announce Type: replace-cross Abstract: Proteins play a vital role in biological processes and are indispensable for living organisms. Accurate representation of proteins is crucial,
arXiv:2605.27766v1 Announce Type: new Abstract: LLM safety evaluations predominantly test models in isolation, yet deployed AI agents increasingly operate within persistent social environments alongsi
Governance should lead to more building, not less Agent development is so much more fun when people don't need to ration tokens because one runaway agent might blow up the bill Understand spend, cap t
arXiv:2605.27799v1 Announce Type: new Abstract: International Classification of Diseases (ICD) is a globally recognized coding system that records diagnostic events during each patient encounter, prov
arXiv:2605.27866v1 Announce Type: new Abstract: Evaluating AI tutor responses requires more than factual correctness: tutors must identify mistakes, locate errors, provide guidance, and offer actionab
arXiv:2605.28124v1 Announce Type: new Abstract: The goal of this work is to reduce the effect of photon noise in dental cone-beam CT reconstruction. We consider an inverse problem formulation and deve
arXiv:2605.27591v1 Announce Type: new Abstract: Many organizations lack computational resources to fine-tune large language models (LLMs) on private (unshareable) data for better utility, while fine-t