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This Week in Sports Trivia: October 16, 2025 https://www.nytimes.com/athletic/6720263/2025/10/16/this-week-in-sports-trivia-october-16-2025/

Sunspot Observations in 1684-1702: John Flamsteed and Philippe de La Hire
Nadezhda Zolotova, Mikhail Vokhmyanin
https://arxiv.org/abs/2510.11375 https://ar…

Sunspot Observations in 1684-1702: John Flamsteed and Philippe de La Hire
In this work, we present an extensive review and detailed analysis of sunspot measurements, drawings, and engravings made by John Flamsteed and, mainly, by Philippe de La Hire during the Maunder minimum. All available information and contemporary knowledge about the sunspot nature are shown. The coordinates, areas, and numbers of sunspots and sunspot groups are reconstructed. Based on these observations, La Hire, Jean-Dominique Cassini, and his son Jacques Cassini regularly published results th…

Observation Matrix Design for Densifying MIMO Channel Estimation via 2D Ice Filling
Zijian Zhang, Mingyao Cui
https://arxiv.org/abs/2510.08887 https://arxi…

Observation Matrix Design for Densifying MIMO Channel Estimation via 2D Ice Filling
In recent years, densifying multiple-input multiple-output (MIMO) has attracted much attention from the communication community. Thanks to the subwavelength antenna spacing, the strong correlations among densifying antennas provide sufficient prior knowledge about channel state information (CSI). This inspires the careful design of observation matrices (e.g., transmit precoders and receive combiners), that exploits the CSI prior knowledge, to boost channel estimation performance. Aligned with t…

Chronologically Consistent Generative AI
Songrun He, Linying Lv, Asaf Manela, Jimmy Wu
https://arxiv.org/abs/2510.11677 https://arxiv.org/pdf/2510.11677

Chronologically Consistent Generative AI
We introduce a family of chronologically consistent, instruction-following large language models to eliminate lookahead bias. Each model is trained only on data available before a clearly defined knowledge-cutoff date, ensuring strict temporal separation from any post-cutoff data. The resulting framework offers (i) a simple, conversational chat interface, (ii) fully open, fixed model weights that guarantee replicability, and (iii) a conservative lower bound on forecast accuracy, isolating the s…

Memory Retrieval and Consolidation in Large Language Models through Function Tokens
Shaohua Zhang, Yuan Lin, Hang Li
https://arxiv.org/abs/2510.08203 https://

Memory Retrieval and Consolidation in Large Language Models through Function Tokens
The remarkable success of large language models (LLMs) stems from their ability to consolidate vast amounts of knowledge into the memory during pre-training and to retrieve it from the memory during inference, enabling advanced capabilities such as knowledge memorization, instruction-following and reasoning. However, the mechanisms of memory retrieval and consolidation in LLMs remain poorly understood. In this paper, we propose the function token hypothesis to explain the workings of LLMs: Duri…

We distinguish "personal unfairness",
-- the view that one’s own economic situation is unfair,
from "social unfairness",
-- the view that the economic situation of others in society is unfair.
Uncertainties associated with the transition to a globalized knowledge economy heighten people’s feelings of personal unfairness
Feelings of personal unfairness increase support for the "populist right"
and feelings about social unfairn…

Left-Wing Populism vs. Right-Wing Populism - What's the Difference? | This vs. That
What's the difference between Left-Wing Populism and Right-Wing Populism? Left-wing populism and right-wing populism are both political movements that aim to...

QuantMind: A Context-Engineering Based Knowledge Framework for Quantitative Finance
Haoxue Wang, Keli Wen, Yuante Li, Qiancheng Qu, Xiangxu Mu, Xinjie Shen, Jiaqi Gao, Chenyang Chang, Chuhan Xie, San Yu Cheung, Zhuoyuan Hu, Xinyu Wang, Sirui Bi, Bi'an Du
https://arxiv.org/abs/2509.21507

QuantMind: A Context-Engineering Based Knowledge Framework for Quantitative Finance
Quantitative research increasingly relies on unstructured financial content such as filings, earnings calls, and research notes, yet existing LLM and RAG pipelines struggle with point-in-time correctness, evidence attribution, and integration into research workflows. To tackle this, We present QuantMind, an intelligent knowledge extraction and retrieval framework tailored to quantitative finance. QuantMind adopts a two-stage architecture: (i) a knowledge extraction stage that transforms heterog…

Join us today for 'Relational Ecologies of Knowledge and Practice: A Workshop of the Epistemic Justice Network', following from the UNESCO Chairs Forum in Dakar.
UKFIET Conference in Oxford, Wednesday, 17 September, 13:30-15:00
We will brainstorm actionable ideas for achieving epistemic justice as we face broader global challenges of opposition, to imagine visions and learn from lived experiences of reparative partnerships for research and knowledge co-creation.

This Week in Sports Trivia: November 6, 2025 https://www.nytimes.com/athletic/6780827/2025/11/06/this-week-in-sports-trivia-november-6-2025/

This Week in Sports Trivia: December 4, 2025 https://www.nytimes.com/athletic/6859227/2025/12/04/this-week-in-sports-trivia-december-4-2025/