The tech revolution that wasn’t
Dwai Banerjee’s new book examines the visionaries who wanted to turn India into a world power at making computers.
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Astronomers pin down the origins of a planetary odd couple
New measurements of a hot Jupiter and its mini-Neptune companion suggest both planets formed surprisingly far away from their host star.
TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models
arXiv:2504.20605v2 Announce Type: replace-cross Abstract: Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives with explicit ethical lessons. We present TF1-EN-3M, to our knowledge the first open dataset…
Split-on-Share: Mixture of Sparse Experts for Task-Agnostic Continual Learning
arXiv:2601.17616v2 Announce Type: replace Abstract: Continual learning in Large Language Models (LLMs) is hindered by the plasticity-stability dilemma, where acquiring new capabilities often leads to catastrophic forgetting of previous knowledge. Existing methods typically treat parameters uniformly, failing to distinguish between…
Schema-Adaptive Tabular Representation Learning with LLMs for Generalizable Multimodal Clinical Reasoning
arXiv:2604.11835v2 Announce Type: replace Abstract: Machine learning for tabular data remains constrained by poor schema generalization, a challenge rooted in the lack of semantic understanding of structured variables. This challenge is particularly acute in domains like clinical medicine, where electronic…
U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning
arXiv:2605.02765v1 Announce Type: cross Abstract: LLMs are increasingly used for end-user task planning, yet their black-box nature limits users’ ability to ensure reliability and control. While recent systems incorporate verification techniques, it remains unclear how users can effectively apply such…
Time-series forecasting through the lens of dynamics
arXiv:2507.15774v2 Announce Type: replace Abstract: While deep learning is facing an homogenization across modalities led by Transformers, they are still challenged by shallow linear models in the time-series forecasting task. Our hypothesis is that models should learn a direct link…
Chart-FR1: Visual Focus-Driven Fine-Grained Reasoning on Dense Charts
arXiv:2605.01882v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown considerable potential in chart understanding and reasoning tasks. However, they still struggle with high information density (HID) charts characterized by multiple subplots, legends, and dense annotations due to…
Can Causal Discovery Algorithms Help in Generating Legal Arguments?
arXiv:2605.02318v1 Announce Type: cross Abstract: In 2011, Judea Pearl received the Turing Award, considered the Nobel Prize in Computing, for fundamental contributions to artificial intelligence through the development of a calculus for probabilistic and causal reasoning. It includes pioneering the…
Linking spatial biology and clinical histology via Haiku
arXiv:2605.00925v1 Announce Type: new Abstract: Integrating molecular, morphological, and clinical data is essential for basic and translational biomedical research, yet systematic frameworks for jointly modeling these modalities remain limited. Here we present Haiku, a tri-modal contrastive learning model trained on…