Knowledge catalogue
arXiv:2607.02383v1 Announce Type: new Abstract: LLM-based retrieval-augmented generation (RAG) is increasingly used for automated fact-checking (AFC) and related tasks. By grounding LLM outputs in ret
arXiv:2607.01819v1 Announce Type: cross Abstract: The Koopman operator has gained considerable attention due to its ability to provide a global linear representation of highly complex dynamical system
arXiv:2607.02513v1 Announce Type: cross Abstract: LLMs memorize sensitive training data, including personally identifiable information (PII), creating a pressing need for reliable post hoc removal met
arXiv:2607.02459v1 Announce Type: new Abstract: Language models are increasingly used to quantify cultural phenomena, but what makes such measurement distinctively cultural? This paper argues that NLP
arXiv:2504.12317v2 Announce Type: replace Abstract: Scientific language is a central infrastructure of knowledge production, but it remains unclear whether large language models (LLMs) are altering no
arXiv:2508.05941v2 Announce Type: replace Abstract: Visuomotor policies trained via behavior cloning are vulnerable to covariate shift, where small deviations from expert trajectories can compound int
arXiv:2504.02327v2 Announce Type: replace Abstract: Natural Language to SQL (NL2SQL) aims to translate natural language queries into executable SQL statements, offering non-expert users intuitive acce
arXiv:2503.24009v3 Announce Type: replace-cross Abstract: Realistic simulation is critical for applications ranging from robotics to animation. Learned simulators have emerged as a possibility to capt
arXiv:2607.02472v1 Announce Type: new Abstract: This paper presents a methodology for learning a control policy to intercept an intruder using the 3D direction unit vector to the intruder and the inte
arXiv:2602.23056v2 Announce Type: replace Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement learni
arXiv:2209.04942v2 Announce Type: replace-cross Abstract: Problem definition: This paper studies the problem of estimating consumer preferences from bundle sales data. Product bundling is a widely use
arXiv:2512.18368v2 Announce Type: replace Abstract: Scaling imitation learning to diverse multi-task robot manipulation remains challenging due to suboptimal demonstrations, behavioral multi-modality,
arXiv:2607.01880v1 Announce Type: new Abstract: Value functions are an essential component in actor-critic based deep reinforcement learning (RL). Conventionally, these functions are trained as a regr
arXiv:2602.18803v2 Announce Type: replace Abstract: We present LoTIS, a model for visual navigation that provides robot-agnostic image-space guidance by localizing a reference RGB trajectory in the ro
arXiv:2607.02466v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions,
arXiv:2602.08638v2 Announce Type: replace-cross Abstract: As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps
arXiv:2507.02964v2 Announce Type: replace-cross Abstract: The increasing scale of AI workloads demands High-Performance Computing (HPC) infrastructure and training methodologies that are both scalable
arXiv:2501.07892v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicit
arXiv:2607.01794v1 Announce Type: cross Abstract: With the rapid development of autonomous aerial systems, Unmanned Aerial Vehicles (UAVs) are increasingly deployed in applications such as inspection,
arXiv:2607.02417v1 Announce Type: cross Abstract: Autonomous robots often need to move their camera before they can act: to inspect an object, reveal an occluded region, or obtain a view that responds
arXiv:2607.01986v1 Announce Type: new Abstract: Multivariate time-series models for prognostics are often evaluated by point prediction accuracy, yet their internal states rarely expose a coherent deg
arXiv:2510.14331v3 Announce Type: replace Abstract: We study program-learning methods that are efficient in both samples and computation. Classical learning theory suggests that when the target admits
arXiv:2607.01247v1 Announce Type: cross Abstract: Open-ended mathematics exams are valuable because they assess reasoning, proof construction, algorithmic thinking, and communication of intermediate s
arXiv:2602.01564v2 Announce Type: replace Abstract: We study the mean-field Langevin descent-ascent (MFL-DA), a coupled optimization dynamics on the space of probability measures for entropically regu
arXiv:2512.02657v2 Announce Type: replace-cross Abstract: Real-world deployment of text-to-image diffusion models requires continual concept removal as new privacy, copyright, or safety obligations ar
Swyx shared enthusiasm about a Greptile flash mob event at Artificial Intelligence Engineering (AIE) that humorously themed around the concept of 'catching bugs,' likely demonstrating Greptile's capab
arXiv:2607.01921v1 Announce Type: cross Abstract: Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channe
Denver-based Luxonis Holding Corp. announced Thursday it raised 14 million in early-stage funding to transform industrial automation with cameras and machine vision, providing a perception layer for r
arXiv:2607.01831v1 Announce Type: cross Abstract: Long-context inference is increasingly common in large language model (LLM) serving, driven by retrieval-augmented generation and agentic systems. In
arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learnin
This changelog entry announces the ability to manage Vercel Flags segments directly through the Vercel Command Line Interface (CLI), enabling developers to create, update, and configure feature flag s
arXiv:2603.28545v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models and world-action models have emerged as central paradigms for general-purpose robotic intelligence, yet their em
arXiv:2607.01830v1 Announce Type: new Abstract: Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a
arXiv:2607.01241v1 Announce Type: cross Abstract: Existing prompt compression methods treat text as flat token sequences, failing to capture the distributed nature of important information, which is o
Meta Platforms Inc. Chief Executive Mark Zuckerberg told employees at an internal town hall meeting that the company’s work on artificial intelligence agents hasn’t progressed as quickly as he had hop
arXiv:2607.01764v1 Announce Type: new Abstract: Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar tha
arXiv:2607.01525v1 Announce Type: cross Abstract: This monograph provides an introduction to mean field reinforcement learning through the lens of Markov decision processes arising from large-populati
arXiv:2607.01336v1 Announce Type: cross Abstract: Neural Quantum States (NQS) are a remarkably expressive class of variational ansatze for quantum many-body wavefunctions, yet little is understood abo
arXiv:2508.16674v2 Announce Type: replace-cross Abstract: Medical report understanding from real-world document images is essential for generating patient-facing explanations and enabling structured i
arXiv:2607.01751v1 Announce Type: cross Abstract: Existing medical video benchmarks primarily evaluate whether a model produces the correct answer, but rarely assess whether it answers at the right ti
arXiv:2602.03315v2 Announce Type: replace Abstract: Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abs
arXiv:2607.01660v1 Announce Type: new Abstract: Hardware impairments in massive multiple-input multiple-output (MIMO) receivers introduce inter-symbol memory and inter-element coupling, severely degra
arXiv:2607.01740v1 Announce Type: new Abstract: Public LLM leaderboards optimise for global average performance and do not capture the specific cognitive demands of financial-services work: a model th
Jeremie Eliahou Ontiveros / SemiAnalysis: Meta could use its compute for its own models, ad scaling, SpaceX-like neocloud deals, and hosting 3rd-party models; it may be close to an Anthropic deal — Zu
M.G. Siegler / Spyglass: Meta getting into the cloud business has been inevitable for a long time, as it seeks to diversify beyond ad revenue and monetize its AI buildout — Their need to diversify the
arXiv:2503.21796v2 Announce Type: replace-cross Abstract: Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence. Furthermore, evidence for self-s
Meta Platforms Inc. is gearing up to release a new version of its flagship Muse Spark artificial intelligence model. Alexandr Wang, the company’s chief AI officer, wrote on X today that the update wil
arXiv:2506.09105v3 Announce Type: replace-cross Abstract: We present MetaTT, a Tensor Train (TT) adapter framework for fine-tuning of pre-trained transformers. MetaTT enables flexible and parameter-ef
arXiv:2603.27313v2 Announce Type: replace Abstract: Disturbance observer-based control has shown promise in robustifying robotic systems against uncertainties. However, tuning such systems remains cha
Gene Maddaus / Variety: Midjourney wants Disney, Universal, and Warner Bros. to reveal in court how they use AI across their companies; studios sued Midjourney in 2025 for infringement — The studios s
arXiv:2607.02015v1 Announce Type: cross Abstract: Mirror Illusion Art is a novel reflection-conditioned 3D illusion where one object yields two target appearances (front and mirror). The task is formu
arXiv:2607.01844v1 Announce Type: cross Abstract: This paper showcases a memory-efficient training stack for Mixture-of-Experts (MoE) models. It is a training paradigm that combines and specializes va
arXiv:2607.01627v1 Announce Type: cross Abstract: Accurate protein-protein interaction (PPI) prediction is central to functional genomics, disease mechanism discovery, and drug development. A difficul
arXiv:2607.01539v1 Announce Type: cross Abstract: This paper studies whether the Metabolic Multi-Agent Optimizer (MMAO) can act as a credible outer-loop optimizer for classification model selection. W
arXiv:2607.01813v1 Announce Type: cross Abstract: Evaluation benchmarks are essential for assessing vision-language models (VLMs), but most multimodal benchmarks are static, making them vulnerable to
arXiv:2607.01814v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) diagnosis, particularly through tongue inspection, faces persistent challenges in subjectivity and reproducibility. T
arXiv:2607.01689v1 Announce Type: cross Abstract: Model merging aims to combine existing single-task solutions into a multi-task solution without additional data-driven fine-tuning.~Most existing appr
arXiv:2607.01982v1 Announce Type: cross Abstract: Using molecular large language models (LLMs) as a unified framework for understanding molecular structures and functions is emerging as a new trend in
Simon Willison shares additional notes and commentary on his blog regarding judgment and decision-making processes. The post likely explores practical considerations or philosophical perspectives on h
arXiv:2606.13723v2 Announce Type: replace-cross Abstract: Intersection-over-Union (IoU), as a pivotal metric for evaluating the spatial alignment between candidate proposals and ground-truth annotatio