Europe
Continual Learning for Instruction Following from Realtime Feedback
We evaluate through thousands of human-agent interactions, demonstrating 15.4% absolute improvement in instruction execution accuracy
One-Shot Object Detection with Co-Attention and Co-Excitation
Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen, Tyng-Luh Liu
This paper aims to tackle the challenging problem of one-shot object detection.
NHS deal with AI firm Palantir called into question after officials' concerns revealed
The June 2025 briefing to Wes Streeting (2nd left) was released under the Freedom of Information Act. The June 2025 briefing to Wes Streeting (2nd left) was released under the Freedom of Information Act. NHS deal with AI firm Palantir called into question after officials' concerns revealed Health officials fear Palantir's reputation will hinder the delivery of a "vital" ยฃ330m NHS contract, according to briefings seen by the Guardian, sparking fresh calls for the deal to be scrapped. In 2023, ministers selected Palantir, a US surveillance technology company that also works for the Israeli military and Donald Trump's ICE operation, to build an AI-enabled data platform to connect disparate health information across the NHS . Now it has emerged that after Keir Starmer demanded faster deployment, Whitehall officials privately warned that the public perception of Palantir would limit its rollout, meaning the contract would not offer value for money.
Learn What Not to Learn: Action Elimination with Deep Reinforcement Learning
Tom Zahavy, Matan Haroush, Nadav Merlis, Daniel J. Mankowitz, Shie Mannor
Deep RL(DRL) tackles the curse of dimensionality due to large state spaces by utilizing a Deep Neural Network (DNN) to approximate the value function and/or the policy.
Sharp Spectral Rates for Koopman Operator Learning Vladimir R. Kostic Istituto Italiano di Tecnologia University of Novi Sad
Learning the Koopman operator and its spectral decomposition from data is enabled by a number of algorithms.
On Robustness of Principal Component Regression
Anish Agarwal, Devavrat Shah, Dennis Shen, Dogyoon Song
Neural Information Processing Systems http://nips.cc/
Fine-tuninglanguagemodelstofindagreementamong humanswithdiversepreferences Appendix
We refer to Table S2 for example questions from each a subset of clusters. Each participant first read the task instructions (see Figure S2), and completed a short comprehension test. The comprehension check was designed to test the participants' knowledge and understanding of key aspectsoftheexperiment. Once all players had joined, the group started the main experiment. In practice, data was collected in batches of around 20 groups (100 participants) in parallel.
Layer-Dependent Importance Sampling for Training Deep and Large Graph Convolutional Networks
Difan Zou, Ziniu Hu, Yewen Wang, Song Jiang, Yizhou Sun, Quanquan Gu
Then,itsamplesafixednumber of nodes by the calculated probability,and recursively conducts such procedure per layer toconstruct the whole computation graph.
On Coresets for Logistic Regression
Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David Woodruff
First, we show the negativeresult that no strongly sublinear sized coresets existforlogisticregression.