Knowledge catalogue
Healthcare AI is moving out of the pilot phase and into production environments, where the gap between a compelling demo and a clinically trustworthy output has never been more consequential. As AI ag
arXiv:2606.04035v1 Announce Type: cross Abstract: We present a systematic study of domain-dependent safety behavior in open-weight LLMs: 7 standardized experiments across 7 ethical domains, testing 5
arXiv:2606.05029v1 Announce Type: cross Abstract: Controlled experiments are the backbone of machine learning research, but at the scale of modern foundation models, they have become prohibitively exp
arXiv:2510.16302v2 Announce Type: replace Abstract: Multi-hop reasoning for question answering (QA) plays a critical role in retrieval-augmented generation (RAG) for modern large language models (LLMs
arXiv:2511.05050v3 Announce Type: replace-cross Abstract: In this study, a scalable online kernel learning framework is proposed for estimating bidirectional causal effects in systems characterized by
arXiv:2606.02902v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) is increasingly applied to de novo molecular design, but choices in data, rewards, and evaluation can yield uneven p
arXiv:2606.03620v1 Announce Type: cross Abstract: Self-distilled policy optimization (SDPO) has become a popular paradigm for LLM post-training, where a model learns from its own predictions condition
arXiv:2409.08958v3 Announce Type: replace-cross Abstract: Physics-informed neural networks (PINNs) have emerged as a powerful deep learning approach for solving partial differential equations (PDEs) i
arXiv:2606.02632v1 Announce Type: cross Abstract: Modern Machine Learning (ML) and Artificial Intelligence (AI) models, especially large language models (LLMs), are increasingly used to generate scien
arXiv:2606.03284v1 Announce Type: new Abstract: Frontier LLMs perform well in Western contexts, but remain poorly tested on underrepresented cultures such as those in Southeast Asia (SEA). Existing NL
arXiv:2503.07265v4 Announce Type: replace-cross Abstract: Text-to-Image (T2I) models are capable of generating high-quality artistic creations and visual content. However, existing research and evalua
arXiv:2407.15510v2 Announce Type: replace Abstract: Abstraction is key to human and artificial intelligence as it allows one to identify common structure in otherwise distinct objects or situations. A
arXiv:2509.06948v3 Announce Type: replace Abstract: Supervised fine-tuning (SFT) and reinforcement learning with verifiable rewards (RLVR) are two widely used post-training paradigms for improving the
arXiv:2602.06033v2 Announce Type: replace Abstract: Pre-trained vision language models do not have good intuitions about the physical world. Recent work has shown that supervised fine-tuning can impro
arXiv:2606.00005v1 Announce Type: new Abstract: We present the Consilium Protocol, a Byzantine Fault Tolerance-derived architecture for structured multi-model AI deliberation that treats inter-model d
arXiv:2606.01269v1 Announce Type: new Abstract: Transitive inference is the challenge of inferring that A < C from knowing only adjacent relations (A < B, B < C). It is solved by humans and animals no
arXiv:2606.00136v1 Announce Type: cross Abstract: The proliferation of adversarial synthetic content, accelerated by Generative AI (GenAI) is rendering traditional reactive detection methods ineffecti
arXiv:2606.01417v1 Announce Type: new Abstract: Turkey's e-Government Gateway (e-Devlet) serves over 68 million registered users with more than 9,200 government services, and is increasingly integrati
arXiv:2606.01934v1 Announce Type: cross Abstract: Large language models achieve remarkable performance via extended chain-of-thought (CoT) reasoning, yet this lengthy process incurs substantial infere
arXiv:2606.01260v1 Announce Type: cross Abstract: Despite being home to more than 1300 ethnic groups and 700 indigenous languages, bias in Large Language Models has not been fully studied in Indonesia
arXiv:2606.00507v1 Announce Type: new Abstract: Recent advances in Speech Large Language Models (Speech LLMs) have significantly enhanced spoken language understanding and reasoning. However, their co
arXiv:2511.20639v3 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) extend large language models (LLMs) from independent single-model reasoning to coordinative system-level intelligenc
arXiv:2606.01432v1 Announce Type: new Abstract: Accurate modeling of leaf spectral reflectance from physiological and biochemical traits is essential for advancing remote sensing applications in plant
arXiv:2606.00033v1 Announce Type: cross Abstract: While mechanistic interpretability (MI) has produced important insights into neural network internals, the field has yet to establish a standardized s
arXiv:2510.03745v2 Announce Type: replace Abstract: Low-discrepancy points are designed to efficiently fill the space in a uniform manner. This uniformity is highly advantageous in many problems in sc
arXiv:2606.01427v1 Announce Type: cross Abstract: Foundation models (FMs) have achieved substantial success in generalizing across tasks without problemspecific training or fine-tuning. However, many
arXiv:2606.00206v1 Announce Type: new Abstract: Post-training quantization (PTQ) is widely used to deploy large language models efficiently, but its effect on reasoning models is not well understood.
arXiv:2602.12984v2 Announce Type: replace Abstract: Scientific reasoning inherently demands integrating sophisticated toolkits to navigate domain-specific knowledge. Yet, current benchmarks largely ov
arXiv:2606.02048v1 Announce Type: new Abstract: We propose a novel computational toolbox that integrates Topological Data Analysis (TDA), Differential Box Counting (DBC), Multifractal Partition (MFP),
arXiv:2509.13805v4 Announce Type: replace-cross Abstract: Foundation models have revolutionized natural language processing through a ``train once, deploy anywhere'' paradigm, where a single pre-train
arXiv:2606.00133v1 Announce Type: new Abstract: World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artifici
arXiv:2605.31058v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has recently emerged as the cornerstone for shaping the remarkable coding abilities of Large Langu
arXiv:2510.27663v3 Announce Type: replace-cross Abstract: Modern imaging techniques heavily rely on Bayesian statistical models to address difficult image reconstruction and restoration tasks. This pa
arXiv:2605.29116v1 Announce Type: new Abstract: When multiple LLM agents solve the same problem, standard practice compresses each agent's reasoning into a majority vote or layered synthesis, treating
ChatGPT diagnosed 40 million people with a disease that was invented as a joke. Not a real disease. Not a misunderstood disease. A completely fictional condition with a fake name, fake papers, and fak
arXiv:2605.29847v1 Announce Type: new Abstract: Reinforcement Learning (RL) has significantly advanced Large Language Models (LLMs) in verifiable domains, but aligning models for open-ended generation
arXiv:2605.30187v1 Announce Type: new Abstract: The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large lang
The Office of Management and Budget proposed major revisions to federal grant administration rules on May 29, 2026, which would rewrite foundational rules governing how federal grant dollars are award
Thanks for the call out and glad to see that our blog inspired the broader community! We at @FireworksAI_HQ have been using delta updates to scale RL globally for about a year. Including Composer 2 &
arXiv:2605.28864v1 Announce Type: new Abstract: The Cognitive Categorical Transformer (CCT) is a 306M-parameter architecture that augments a pretrained GPT-2 Small backbone with cognitively grounded c
arXiv:2603.23971v2 Announce Type: replace-cross Abstract: Developers and consumers increasingly choose reasoning models (RMs) based on their listed API prices. However, how accurately do these prices
arXiv:2605.29420v1 Announce Type: new Abstract: Persona prompting is widely used to steer large language models, yet its practical value remains unclear. Prior work often evaluates persona prompting u
arXiv:2605.30346v1 Announce Type: new Abstract: As video diffusion models (VDMs) advance toward world models, a key question arises: do they truly understand causality, or merely overfit to statistica
Google Research at I/O 2026 showcased new Gemini AI models including Gemini Omni, which can create content from any input starting with video, and Gemini 3.5 Flash, combining frontier intelligence wit
Google’s mission is to organize the world’s information and make it universally accessible. In high-growth, technically ambitious markets like the Middle East, North Africa, and Türkiye (MENA-T), we f
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:2605.27864v1 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:2605.27499v1 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:2605.28315v1 Announce Type: new Abstract: General-purpose machine translation benchmarks such as FLORES-200 have reached a saturation regime on Chinese-English pairs, where modern large language
Researchers say they’ve found a new way to extract lithium, a crucial metal used in the lithium-ion batteries that power electric vehicles and energy storage arrays. This new technique could be more e
arXiv:2605.28398v1 Announce Type: new Abstract: Hybrid-reasoning large language models (LLMs) expose explicit controls over reasoning effort, allowing users or systems to trade off answer quality agai
arXiv:2605.28405v1 Announce Type: new Abstract: Despite widespread discussion of AGI, there is no clear framework for measuring progress toward it. This ambiguity fuels subjective claims, makes it dif
@OpenAI Foundation just launched with a 25B commitment and equity in OpenAI valued at ~130B. Sounds like a philanthropy giant. But look closer: the big money goes to programs they control internally (
arXiv:2512.08371v4 Announce Type: replace Abstract: Datasets may contain observations with multiple labels. If the labels are not mutually exclusive, and if the labels vary greatly in frequency, obtai
arXiv:2605.26662v1 Announce Type: cross Abstract: This paper examines how estimates of AI use in scientific writing can be biased when evaluation methods ignore contextual differences across countries
Been using Grok Build these past few days, and the thing that really got me hooked is Imagine and Imagine Video. I built a full dinosaur encyclopedia site — every image, every video clip on it, all ge
arXiv:2605.26445v1 Announce Type: new Abstract: Physicians learn primarily about illicit drugs from clinical overdose cases, limiting their understanding of real-world usage. Meanwhile, drug users sha
arXiv:2605.27133v1 Announce Type: cross Abstract: Deep unfolding neural networks derived from iterative optimization schemes and numerical ordinary/partial differential equations (ODEs/PDEs) have attr
arXiv:2506.09398v3 Announce Type: replace Abstract: We consider the task of predicting Hamiltonian matrices to accelerate electronic structure calculations, which plays an important role in physics, c
arXiv:2605.26184v1 Announce Type: cross Abstract: Hybrid post-training usually combines supervised fine-tuning and reinforcement learning, but fixed mixing schedules cannot adapt when the relative noi