Knowledge catalogue
arXiv:2606.02747v1 Announce Type: cross Abstract: Planning records define restrictions over geographic areas, but their source documents often provide only indirect spatial evidence rather than machin
arXiv:2403.19883v2 Announce Type: replace Abstract: Fully-observable non-deterministic (FOND) planning is at the core of artificial intelligence planning with uncertainty. It models uncertainty throug
arXiv:2502.02260v2 Announce Type: replace Abstract: In the past decade, considerable research effort has been devoted to securing machine learning (ML) models that operate in adversarial settings. Yet
DigitalOcean discusses infrastructure and platform capabilities designed to support the inference phase of machine learning, where trained models are deployed to make predictions on new data at scale.
arXiv:2510.17149v3 Announce Type: replace Abstract: As large-scale multi-agent systems evolve, the communication protocol layer has become a critical yet under-evaluated factor shaping performance and
arXiv:2606.03136v1 Announce Type: cross Abstract: Multi-turn jailbreak attacks on large language models (LLMs) reveal a mismatch in current guardrails: they operate on individual turns, while attacks
arXiv:2606.03019v1 Announce Type: cross Abstract: Copyleft, as implemented in licenses such as the GNU General Public License, was a legal hack that used copyright to guarantee user freedom by tying t
arXiv:2606.03817v1 Announce Type: new Abstract: Idioms can be analysed in terms of their decomposability, the extent to which constituent meanings contribute to the figurative whole. Decomposability i
arXiv:2606.03234v1 Announce Type: new Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has become the dominant approach for improving mathematical reasoning in large language models, ye
arXiv:2606.03069v1 Announce Type: cross Abstract: Generalized segmentation of medical images prevents performance degradation when different imaging devices and clinical protocols are used across mult
arXiv:2606.02886v1 Announce Type: cross Abstract: Deep learning weather models now match numerical weather prediction accuracy while running orders of magnitude faster, but produce deterministic forec
arXiv:2606.02740v1 Announce Type: cross Abstract: Gradient boosted decision trees require a stopping rule to avoid overfitting. The standard rule monitors a validation loss and stops if the loss fails
shower thought If: 1. AI is smarter than humans at law, therapy, etc. 2. Humans still like talking to other humans. Then: Humans are just an AI wrapper. Everyone should just regurgitate what Claude te
Kate Clark / Wall Street Journal: Sources: Benchmark raised 2B across two new funds, including a 1.25B fund for late-stage bets, its first growth fund after decades focusing on new startups — After a
Reuters: Sources: DeepSeek is set to raise ~7.4B in its first funding round from investors including Tencent and CATL at a valuation of between ~52B and ~59B — Chinese AI startup DeepSeek is set to ra
arXiv:2606.03332v1 Announce Type: new Abstract: Probabilistic models are typically trained using task-agnostic objectives like log-loss, which can lead to significant errors in downstream estimation.
arXiv:2511.04421v2 Announce Type: replace Abstract: Action chunking is a widely adopted approach in Learning from Demonstration (LfD). By modeling multi-step action chunks rather than single-step acti
arXiv:2606.03806v1 Announce Type: new Abstract: Temperature-emissivity-texture (TeX) decomposition seeks to recover object heat state, material spectral response, and visible-like geometric texture fr
arXiv:2606.03839v1 Announce Type: new Abstract: Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description. TAG models usually train a Graph Neur
arXiv:2606.03043v1 Announce Type: new Abstract: LMs-as-judges are now standard, yet judges agree strongly with one another while agreeing only weakly with humans. We test whether this reflects shared
arXiv:2606.03907v1 Announce Type: cross Abstract: Agentic AI coding tools write code with increasing autonomy and in doing so decide when to import a library and when to implement functionality from s
arXiv:2606.02646v1 Announce Type: cross Abstract: Inference-time multi-agent LLM scaling lacks a shared unit: counting nominal agents conflates cost with independent evidence. We derive a two-paramete
arXiv:2606.03092v1 Announce Type: new Abstract: Inference-time scaling has emerged as a critical avenue for enhancing Large Language Models' performance, yet real-world deployment is constrained by st
This is really intellectually dishonest. I have not been arguing that LLM token prices are increasing (though the all you can eat buffet is over), I have been arguing the *opposite*, viz that they wil
This story was so implausible that the only way it even (kind of) made sense if it is some sort of internal accounting placeholder at a cloud provider using their own compute. And even then it seems u
thought I was supposed to be the shit-posting account here shower thought If: 1. AI is smarter than humans at law, therapy, etc. 2. Humans still like talking to other humans. Then: Humans are just an
arXiv:2606.03762v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) equips large language models (LLMs) with tool-use capabilities that substantially improve reasoning on complex tas
arXiv:2606.03462v1 Announce Type: new Abstract: Graph neural networks have achieved strong performance on graph-structured data, but their effectiveness depends heavily on the quality of the observed
arXiv:2606.02862v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive
arXiv:2606.03490v1 Announce Type: new Abstract: Modern action recognition models operate on memory- and compute-intensive dense RGB video volumes and frequently exploit appearance and background short
arXiv:2606.03584v1 Announce Type: new Abstract: Equilibrium Propagation (EP) is a physics-based training framework that has primarily been employed in energy-based models, including continuous Hopfiel
arXiv:2603.23117v2 Announce Type: cross Abstract: By integrating Chain-of-Thought (CoT) reasoning, Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation, pa
Uber Caps Usage of AI Tools Like Claude Code to Manage Costs I wrote the other day about Uber blowing its 2026 AI budget in four months, and how that wasn't particularly surprising given they would ha
Ollama v0.30.2 is a patch release from the 0.30 series, which features improved compatibility and performance using llama.cpp, augmented MLX engine support on Apple Silicon, and broader model support
This release candidate fixes a Windows-specific issue where the llama-server process wasn't being properly terminated during cleanup operations. The fix addresses GitHub issue #16458 and improves the
arXiv:2606.03954v1 Announce Type: new Abstract: As AI systems increasingly assist humans in physical tasks, ensuring safety becomes paramount -- physical actions carry immediate and irreversible conse
arXiv:2603.04956v2 Announce Type: replace Abstract: This paper considers the problem of converting a given dense linear layer to low precision. The tradeoff between compressed length and output discre
arXiv:2606.03461v1 Announce Type: new Abstract: Stronger code agents are commonly assumed to be superior teachers for post-training, yet this assumption remains poorly disentangled from task difficult
arXiv:2606.02866v1 Announce Type: new Abstract: When does multi-agent debate help data cleaning, and when does it hurt? Across three benchmarks, four model families, and over 6,000 task-condition pair
arXiv:2606.03532v1 Announce Type: cross Abstract: Self on-policy distillation trains a student policy against a teacher derived from its own parameter history, yet the teacher's update schedule -- whi
arXiv:2603.03612v3 Announce Type: replace-cross Abstract: The community is increasingly exploring linear RNNs (LRNNs) as language models, motivated by their expressive power and parallelizability. Whi
arXiv:2606.03038v1 Announce Type: new Abstract: Neural field surrogates can accelerate photonic design loops, but a surrogate that looks accurate in global field error can still mis-rank candidate dev
This post documents a completed Wordle puzzle (puzzle #1,809) solved in five attempts, showing the progression of letter guesses through color-coded feedback (yellow for correct letters in wrong posit
arXiv:2606.01933v1 Announce Type: new Abstract: This paper presents our winning methodology for the CASTLE 2026 Challenge at the CVPR 2026 EgoVis Workshop, where our team secured third place globally.
arXiv:2606.01034v1 Announce Type: new Abstract: We study when LLM judge panels should be calibrated with low-dimensional stackers versus joint output tables under finite human-label budgets. Low-dimen
arXiv:2606.00106v1 Announce Type: cross Abstract: Brain-computer interfaces (BCIs) are limited by low signal-to-noise ratio in modalities such as electroencephalography, which requires multiple trials
arXiv:2507.12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient asses
arXiv:2606.01122v1 Announce Type: new Abstract: We propose a five-step diagnostic protocol for residual-trained neural HJB-PIDE solvers with control-dependent Levy jumps, targeting a general failure m
arXiv:2606.02113v1 Announce Type: cross Abstract: Post-training has become a primary driver of recent progress in large reasoning models, and reasoning data are often the key variable determining whet
arXiv:2606.01861v1 Announce Type: new Abstract: Self-play, a type of training algorithm that enables a model to self-improve, has recently shown promising empirical results in the context of formal th
Many data engineers spend significant time managing compatibility and getting best performance across multiple analytics engines. To help solve this pain point, we are excited to announce gcs-analytic
arXiv:2606.01110v1 Announce Type: cross Abstract: Full waveform inversion (FWI) reconstructs heterogeneous material properties from receiver data but remains computationally demanding. Physics-informe
arXiv:2512.00986v3 Announce Type: replace Abstract: A surge in academic publications calls for automated deep research (DR) systems, but accurately evaluating them is still an open problem. First, exi
arXiv:2606.00914v1 Announce Type: new Abstract: LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queu
arXiv:2606.01508v1 Announce Type: cross Abstract: Traditional operating systems were designed around deterministic programs, explicit control flow, and human initiated workflows. Their core abstractio
arXiv:2606.02461v1 Announce Type: new Abstract: Language agents spend substantial inference time solving individual tasks, yet the experience acquired in one episode is often underutilized in future e
arXiv:2606.01362v1 Announce Type: cross Abstract: Video generative models have achieved remarkable progress in synthesizing photorealistic video sequences. However, enabling broader and more creative
arXiv:2602.08868v2 Announce Type: replace-cross Abstract: Time-series anomaly detection (TSAD) with multimodal large language models (MLLMs) is an emerging area, yet a persistent challenge remains: ML
arXiv:2606.01044v1 Announce Type: new Abstract: Medical visual question answering requires models to ground their responses in image evidence, because visually unsupported answers can mislead downstre
arXiv:2601.00664v2 Announce Type: replace-cross Abstract: Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models