Search: “science”

arXiv:2601.09716v2 Announce Type: replace Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepre

arXiv:2608.14625v1 Announce Type: cross Abstract: Academic peer review is under mounting strain: NeurIPS 2025 received 21,575 submissions, ICLR 2025 received 11,603, and ICML 2025 received 12,107. Thi

arXiv:2608.11403v1 Announce Type: new Abstract: Self-consistency (SC) via majority vote is a widely used way to spend inference-time compute: sample N chains of thought, return the plurality answer. O

arXiv:2506.03922v4 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated significant potential to advance a broad range of domains. However, current benchma

arXiv:2607.16235v3 Announce Type: replace-cross Abstract: Mobile and wearable devices offer an unprecedented opportunity for continuous, passive health monitoring and active health coaching. However,

arXiv:2607.24795v1 Announce Type: new Abstract: Older adults' independent mobility enables out-of-home participation, well-being and health, yet pedestrian navigation systems still optimize primarily

arXiv:2505.07889v4 Announce Type: replace Abstract: The realization of autonomous scientific experimentation is currently limited by LLMs' struggle to grasp the strict procedural logic and accuracy re

arXiv:2607.22513v1 Announce Type: cross Abstract: Commercial large language models are increasingly used as knowledge references, yet their stance on contested scientific claims is neither stable nor

arXiv:2607.20058v1 Announce Type: new Abstract: Large language models can answer scientific questions, yet a correct output does not reveal whether the model represents or uses the governing physics.

arXiv:2606.26525v1 Announce Type: new Abstract: Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-f

arXiv:2606.25320v1 Announce Type: cross Abstract: Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Inform

arXiv:2606.24104v1 Announce Type: cross Abstract: Generative artificial intelligence(GenAI) is reshaping learning in higher education, with particularly pronounced implications for the humanities and

The NVIDIA BioNeMo Agent Toolkit enables AI scientists to use structure prediction, molecular generation, docking, sequence analysis, design, and genomics as callable tools , allowing AI agents to exe

Programming is fundamentally about managing complexity through abstraction layers rather than merely writing code, analogous to how music transcends its written notation. This perspective, shared by A

arXiv:2606.09198v1 Announce Type: new Abstract: Deep Research agents powered by Large Language Models (LLMs) have exhibited extraordinary potential in automated paper writing tasks. However, existing

arXiv:2606.01316v1 Announce Type: new Abstract: Scientific discovery demands intelligence, perseverance, and serendipity across vast search spaces. Today, top scientific capabilities remain siloed--on

arXiv:2606.01444v1 Announce Type: new Abstract: Scientific discovery is not only answer generation but revision of the representational regime in which evidence, artifacts, operations, and verifiers a

arXiv:2605.29741v1 Announce Type: new Abstract: The dominance of colonial languages in African education and scientific communication limits how hundreds of millions of speakers of African languages a

arXiv:2605.29249v1 Announce Type: cross Abstract: Many applications require statistically valid inference across many related tasks, while using only a handful of high-quality labels per hypothesis. I

arXiv:2605.16286v1 Announce Type: cross Abstract: Different AI tools such as ChatGPT, Gemini, and Claude are becoming very popular. Although they are helpful for many day-to-day tasks, they can be use

arXiv:2508.15878v2 Announce Type: replace-cross Abstract: Formal theorem proving (FTP) has emerged as a critical foundation for evaluating the reasoning capabilities of large language models, enabling

arXiv:2602.19770v2 Announce Type: replace Abstract: Explainable artificial intelligence has emerged as a promising field of research to address reliability concerns in artificial intelligence. Despite

arXiv:2605.09534v1 Announce Type: cross Abstract: Engineering managers increasingly must decide how to introduce generative artificial intelligence (AI), retrieval-augmented generation, and coding age

arXiv:2605.10754v1 Announce Type: new Abstract: LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Inexpensive seafloor-hopping submersibles could stoke deep-sea

The artificial intelligence era is widening the gap between winners and laggards, and the delta is not only determined by who has the most AI but also how deeply AI is embedded into business processes

arXiv:2604.23002v1 Announce Type: new Abstract: Formalising informal mathematical reasoning into formally verifiable code is a significant challenge for large language models. In scientific fields suc

Artificial intelligence-based human resources company Phenom People Inc. announced today that it has acquired Plum.io Inc., a psychometric-based talent assessments company that measures the durable sk

arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s

arXiv:2602.08561v3 Announce Type: replace-cross Abstract: Reproducing computational research is often assumed to be as simple as rerunning the original code with provided data. In practice, missing pa

arXiv:2604.20658v1 Announce Type: new Abstract: Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solvin

arXiv:2604.10524v1 Announce Type: new Abstract: In medical image segmentation across multiple modalities (e.g., MRI, CT, etc.) and heterogeneous data sources (e.g., different hospitals and devices), D

arXiv:2604.11261v1 Announce Type: new Abstract: This paper introduces AI as a Research Object (AI-RO), a paradigm for governing the use of generative AI in scientific research. Instead of debating whe

arXiv:2604.10718v1 Announce Type: new Abstract: Accelerating scientific discovery requires the identification of which experiments would yield the best outcomes before committing resources to costly p

EinsteinArena is a platform where AI agents collaborate and compete on open math problems. AI agents on EinsteinArena have already set 11 new state-of-the-art results on open math problems — including

arXiv:2602.11354v2 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scientific papers. Existing benchmarks focus primarily on

This r/StableDiffusion post explores the nuanced and often empirical process of training LoRA (Low-Rank Adaptation) models on Stable Diffusion XL (SDXL), a fine-tuning technique that, rather than retr

Imagine your compliance team notices that payments are taking longer than expected to clear. They suspect fraud, and you’re the data scientist helping figure out which transactions to investigate firs

arXiv:2610.09446v1 Announce Type: new Abstract: Large language models (LLMs) should abstain from scientific multiple-choice questions when no option is valid, but frequent abstention alone does not de

arXiv:2610.09237v1 Announce Type: cross Abstract: Scientific studies of language agents need behavioral variables that support hypotheses across tasks and models. We formulate this research problem as

arXiv:2602.03915v2 Announce Type: replace-cross Abstract: Tokens are discrete representations that allow modern deep learning to scale by transforming high-dimensional data into sequences that can be

arXiv:2609.33347v1 Announce Type: new Abstract: World models can be studied as experimental systems with response laws of their own. We introduce MultiEcho, a framework for estimating these laws throu

arXiv:2604.07530v3 Announce Type: replace-cross Abstract: Scaling laws describe how language model capabilities grow with compute and data, but say nothing about how long a model matters once released

arXiv:2609.29333v1 Announce Type: cross Abstract: One long-form exam in a large course costs hundreds of grader-hours, and qualified graders are scarce; LLM graders are a tempting alternative. To show

arXiv:2505.17640v3 Announce Type: replace Abstract: Time series segmentation assigns a label to each part of a sequence. We formulate dense univariate segmentation as node classification on a graph wh

arXiv:2609.20166v1 Announce Type: new Abstract: Tiny transformers trained on fully-enumerable tasks occupy an unusual position in the study of grokking: every input can be evaluated, every generalizat