Knowledge catalogue
Amazon Bedrock now supports cost allocation by IAM principal (users and roles) in AWS Cost and Usage Report 2.0 and Cost Explorer, enabling customers to understand and attribute inference costs across
arXiv:2506.19807v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an in
arXiv:2502.16761v2 Announce Type: replace Abstract: Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stage
arXiv:2509.23638v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) models face memory and PCIe latency bottlenecks when deployed on commodity hardware. Offloading expert weights to CPU memor
arXiv:2512.17091v2 Announce Type: replace Abstract: We propose a new approach for solving planning problems with a hierarchical structure, fusing reinforcement learning and MPC planning. Our formulati
arXiv:2604.15203v1 Announce Type: new Abstract: Machine learning in high-stakes domains such as healthcare requires not only strong predictive performance but also reliable uncertainty quantification
arXiv:2604.14562v1 Announce Type: new Abstract: Accurate thermal modeling in metal additive manufacturing (AM) is essential for understanding the process-structure-performance relationship. While prio
arXiv:2602.07529v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong performance and rapid progress in a wide range of medical reasoning tasks. However, their sequ
arXiv:2601.08310v2 Announce Type: replace Abstract: Recent Large Reasoning Models (LRMs) achieve strong performance by leveraging long-form Chain-of-Thought (CoT) reasoning, but uniformly applying ove
arXiv:2604.13037v1 Announce Type: cross Abstract: Mining multiple longest common subsequences (extit{MLCS}) from a set of sequences of three or more over a finite alphabet Sigma (a classical NP-hard p
arXiv:2604.14175v1 Announce Type: new Abstract: We present a unified system addressing both Subtask 3 (answer generation) and Subtask 4 (evidence sentence alignment) of the ArchEHR-QA Shared Task. For
arXiv:2604.14265v1 Announce Type: new Abstract: We study behavior-regularized reinforcement learning (RL), where regularization toward a reference distribution (the dataset in offline RL or the base m
arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy
arXiv:2604.05302v2 Announce Type: replace Abstract: Text simplification supports second language (L2) learning by providing comprehensible input, consistent with the Input Hypothesis. However, constru
arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab
arXiv:2604.14163v1 Announce Type: new Abstract: Maritime distress communications transmitted over very high frequency (VHF) radio are safety-critical voice messages used to report emergencies at sea.
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:2510.07890v3 Announce Type: replace Abstract: Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are pri
arXiv:2604.13417v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly deployed in mission-critical software systems, detecting hallucinations and ``faked truthfulness'' ha
DigitalOcean's Inference Cloud Memory Layer is a technical architecture component designed to optimize database performance by implementing an in-memory caching layer for faster data access and reduce
arXiv:2604.14345v1 Announce Type: new Abstract: As search depth increases in autonomous reasoning and embodied planning, the candidate action space expands exponentially, heavily taxing computational
arXiv:2506.08080v2 Announce Type: replace-cross Abstract: Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A
arXiv:2604.14209v1 Announce Type: new Abstract: As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that ar
arXiv:2601.03523v2 Announce Type: replace Abstract: One of the most important queries in knowledge compilation is weighted model counting (WMC), which has been applied to probabilistic inference on va
Vultr CEO J.J. Kardwell discusses the current shortage of AI computing capacity, potential solutions to address infrastructure constraints, and how customer demand patterns for AI services are evolvin
arXiv:2603.29088v2 Announce Type: replace-cross Abstract: Recent progress in large language models (LLMs) has substantially advanced automatic code generation and formal theorem proving, yet software
arXiv:2604.13381v1 Announce Type: cross Abstract: Conversational generative artificial intelligence agents (or genAI chatbots) could benefit youth mental health, yet young people's perspectives remain
A deep mystery to me is that if I upload writing to a chatbot and ask it for a list of individual improvements, basically everything it gives me makes the text more punchy and direct and nice to read.
arXiv:2604.13240v1 Announce Type: new Abstract: Mapping the spatial distribution of species is essential for conservation policy and invasive species management. Species distribution models (SDMs) are
arXiv:2604.13085v1 Announce Type: new Abstract: Autonomous AI agents operating in dynamic environments face a persistent challenge: acquiring new capabilities without erasing prior knowledge. We prese
arXiv:2604.13924v1 Announce Type: cross Abstract: Time-series anomaly detection (TSAD) is critical in domains such as industrial monitoring, healthcare, and cybersecurity, but it remains challenging d
arXiv:2604.13846v1 Announce Type: new Abstract: Personalized Large Language Models (LLMs) facilitate more natural, human-like interactions in human-centric applications. However, existing personalizat
arXiv:2506.20083v4 Announce Type: replace Abstract: Integrating compositional and symbolic properties into current distributional semantic spaces can enhance the interpretability, controllability, com
arXiv:2604.13107v1 Announce Type: cross Abstract: As coding agents have seen rapid capability and adoption gains, users are applying them to general tasks beyond software engineering. In this post, we
Codex Compute is a service promoted as offering reliable, always-available computing infrastructure with strong engineering capabilities and an application that extends functionality beyond traditiona
This Reddit thread from r/ChatGPT likely reflects common user confusion around what the ChatGPT Plus subscription ($20/month) includes, particularly regarding model access, usage limits, and how it co
arXiv:2510.26491v2 Announce Type: replace Abstract: Data selection is a critical aspect of Reinforcement Learning with Verifiable Rewards (RLVR) for enhancing the reasoning capabilities of large langu
arXiv:2604.14053v1 Announce Type: new Abstract: Efficiency and safety of Large Language Models (LLMs), among other factors, rely on the quality of tokenization. A good tokenizer not only improves infe
arXiv:2604.13288v1 Announce Type: new Abstract: We present a unified pipeline for synthesizing high-quality Quechua and Spanish speech for the Peruvian Constitution using three state-of-the-art text-t
arXiv:2604.13942v1 Announce Type: new Abstract: Recent vision-language-action (VLA) systems have demonstrated strong capabilities in embodied manipulation. However, most existing VLA policies rely on
arXiv:2604.13871v1 Announce Type: new Abstract: Deep neural networks (DNNs) deliver state-of-the-art accuracy on regression and classification tasks, yet two structural deficits persistently obstruct
HOLY 🤯 The one and only @elder_plinius just dropped an unlocked Gemma 4 E4B, and the specs are INSANE. Look at the performance shifts: → Refusal rate: 98.8% down to 2.1% (!!) → Compliance: 1.2% up to
arXiv:2604.13686v1 Announce Type: new Abstract: While Large Language Models (LLMs) have significantly advanced Text-to-SQL performance, existing benchmarks predominantly focus on Western contexts and
GPT-Rosalind is a frontier reasoning model developed by OpenAI, specifically designed to support research applications in biology, drug discovery, and translational medicine. The model was introduced
arXiv:2512.10605v2 Announce Type: replace Abstract: We propose LEO-RobotAgent, a general-purpose language-driven intelligent agent framework for robots. Under this framework, LLMs can operate differen
Lots of major improvements to Codex! Computer use is a real update for me; it feels even more useful than I expected. It can use all of the apps on your Mac, in parallel and without interfering with y
arXiv:2604.13695v1 Announce Type: new Abstract: Reliable and interpretable decision-making is essential in medical imaging, where diagnostic outcomes directly influence patient care. Despite advances
arXiv:2604.14004v1 Announce Type: cross Abstract: Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization
arXiv:2604.13828v1 Announce Type: new Abstract: User simulators are essential for the scalable training and evaluation of interactive AI systems. However, existing approaches often rely on shallow use
arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal
arXiv:2604.14073v1 Announce Type: new Abstract: Resolving and rewriting references is fundamental in programming languages. Motivated by a real-world decompilation task, we abstract reference rewritin
arXiv:2601.11340v2 Announce Type: replace Abstract: Chain-of-Thought reasoning has significantly enhanced the problem-solving capabilities of Large Language Models. Unfortunately, current models gener
OpenAI's Codex now features background computer use that lets multiple AI agents operate a Mac simultaneously without disrupting the user's own work. The update allows Codex to access all other apps o
arXiv:2602.07924v2 Announce Type: replace Abstract: Securing petroleum infrastructure requires balancing autonomous system efficiency with human judgment for threat escalation, a challenge unaddressed
arXiv:2604.13356v1 Announce Type: new Abstract: Mechanisms for continued self-improvement of language models without external supervision remain an open challenge. We propose Peer-Predictive Self-Trai
People have been asking for this for years. It wasn't clear how to make it performant enough to be shippable, until earlier today In the next version of Bun `bun test` gets experimental support for pe
Publishers have real questions about AI, but let’s be clear: @waybackmachine isn’t a backdoor for AI scraping. For 30 years, it’s been built for people, not bulk harvesting. We actively monitor to pre
For anyone who has been (inadvisably) taking my pelican riding a bicycle benchmark seriously as a robust way to test models, here are pelicans from this morning's two big model releases - Qwen3.6-35B-
arXiv:2604.13602v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and multi
arXiv:2604.13236v1 Announce Type: new Abstract: Semiconductor failure analysis (FA) requires engineers to examine inspection images, correlate equipment telemetry, consult historical defect records, a