Gemma 3 Technical Report
Gemma Team Aishwarya Kamath
Johan Ferret
Shreya Pathak
Nino Vieillard
Ramona Merhej
Sarah Perrin
Tatiana Matejovicova
Alexandre Ram'e
Morgane Rivière
Louis Rouillard
Thomas Mesnard
Geoffrey Cideron
Jean-Bastien Grill
Sabela Ramos
Edouard Yvinec
Michelle Casbon
Etienne Pot
Ivo Penchev
Gael Liu
Francesco Visin … (voir 190 de plus)
Kathleen Kenealy
Lucas Beyer
Xiaohai Zhai
Anton Tsitsulin
Róbert Busa-Fekete
Alex Feng
Noveen Sachdeva
Benjamin Coleman
Yi Gao
Basil Mustafa
Iain Barr
Emilio Parisotto
David Tian
Matan Eyal
Colin Cherry
Jan-Thorsten Peter
Danila Sinopalnikov
Surya Bhupatiraju
Mehran Kazemi
Dan Malkin
Ravin Kumar
David Vilar
Idan Brusilovsky
Jiaming Luo
Andreas Steiner
Abe Friesen
Abhanshu Sharma
Abheesht Sharma
Adi Mayrav Gilady
Adrian Goedeckemeyer
Alaa Saade
Alexander Kolesnikov
Alexei Bendebury
Alvin Abdagic
Amit Vadi
Andr'as Gyorgy
André Susano Pinto
Anil Das
Ankur Bapna
Antoine Miech
Antoine Yang
Antonia Paterson
Ashish Shenoy
Ayan Chakrabarti
Bilal Piot
Boxi Wu
Bobak Shahriari
Bryce Petrini
Charlie Chen
Charline Le Lan
Christopher A. Choquette-Choo
CJ Carey
Cormac Brick
Daniel Deutsch
Danielle Eisenbud
Dee Cattle
Derek Cheng
Dimitris Paparas
Divyashree Shivakumar Sreepathihalli
Doug Reid
Dustin Tran
Dustin Zelle
Eric Noland
Erwin Huizenga
Eugene Kharitonov
Frederick Liu
Gagik Amirkhanyan
Glenn Cameron
Hadi Hashemi
Hanna Klimczak-Pluci'nska
Harman Singh
Harsh Mehta
Harshal Tushar Lehri
Hussein Hazimeh
Ian Ballantyne
Idan Szpektor
Ivan Nardini
Jean Pouget-Abadie
Jetha Chan
Joe Stanton
J. Michael Wieting
Jonathan Lai
Jordi Orbay
Joe Fernandez
Joshua Newlan
Junsong Ji
Jyotinder Singh
Kat Black
Kathy Yu
Kevin Hui
Kiran N. Vodrahalli
Klaus Greff
Linhai Qiu
Marcella Valentine
Marina Coelho
Marvin Ritter
Matt Hoffman
Matthew Watson
Mayank Chaturvedi
Michael Moynihan
Min Ma
Nabila Babar
Natasha Noy
Nathan Byrd
Nick Roy
Nikola Momchev
Nilay Chauhan
Oskar Bunyan
Pankil Botarda
Paul Caron
Paul Kishan Rubenstein
Phil Culliton
Philipp Schmid
Pier Giuseppe Sessa
Pingmei Xu
Piotr Stańczyk
Pouya Dehghani Tafti
Rakesh Shivanna
Renjie Wu
Renke Pan
R. Rokni
Rob Willoughby
Rohith Vallu
Ryan Mullins
Sammy Jerome
Sara Smoot
Sertan Girgin
Shariq Iqbal
Shashir Reddy
Shruti Sheth
Siim Põder
Sijal Bhatnagar
S. Panyam
Sivan Eiger
Susan Zhang
Tianqi Liu
Trevor Yacovone
T. Liechty
Uday Kalra
Utku Evci
Vedant Misra
Vincent Roseberry
Vladimir Feinberg
Vlad Kolesnikov
Woohyun Han
Woosuk Kwon
X. T. Chen
Yinlam Chow
Yuvein Zhu
Zichuan Wei
Z. Egyed
Victor Cotruta
Minh Giang
Phoebe Kirk
Anand Rao
Jessica Lo
Erica Moreira
Luiz GUStavo Martins
Omar Sanseviero
Lucas Gonzalez
Zach Gleicher
Tris Brian Warkentin
Seyed Vahab Mirrokni
Evan Senter
Eli Collins
Joelle Barral
Zoubin Ghahramani
Raia Hadsell
Yossi Matias
D. Sculley
Slav Petrov
Noah Fiedel
Noam M. Shazeer
Oriol Vinyals
Jeffrey Dean
Demis Hassabis
Koray Kavukcuoglu
Clément Farabet
Elena Buchatskaya
Jean-Baptiste Alayrac
Rohan Anil
Dmitry Lepikhin
Sebastian Borgeaud
Olivier Bachem
Armand Joulin
Alek Andreev
Cassidy Hardin
Robert Dadashi
L'eonard Hussenot
A scalable gene network model of regulatory dynamics in single cells
Paul Bertin
Joseph D Viviano
Alejandro Tejada-Lapuerta
Weixu Wang
Stefan Bauer
Fabian J. Theis
A scalable gene network model of regulatory dynamics in single cells
Paul Bertin
Joseph D Viviano
Alejandro Tejada-Lapuerta
Weixu Wang
Stefan Bauer
Fabian J. Theis
Capturing Individual Human Preferences with Reward Features
Andr'e Barreto
Vincent Dumoulin
Yiran Mao
Nicolas Perez-Nieves
Bobak Shahriari
Yann Dauphin
Capturing Individual Human Preferences with Reward Features
Andre Barreto
Vincent Dumoulin
Yiran Mao
Nicolas Perez-Nieves
Bobak Shahriari
Yann Dauphin
Reinforcement learning from human feedback usually models preferences using a reward model that does not distinguish between people. We argu… (voir plus)e that this is unlikely to be a good design choice in contexts with high potential for disagreement, like in the training of large language models. We propose a method to specialise a reward model to a person or group of people. Our approach builds on the observation that individual preferences can be captured as a linear combination of a set of general reward features. We show how to learn such features and subsequently use them to quickly adapt the reward model to a specific individual, even if their preferences are not reflected in the training data. We present experiments with large language models comparing the proposed architecture with a non-adaptive reward model and also adaptive counterparts, including models that do in-context personalisation. Depending on how much disagreement there is in the training data, our model either significantly outperforms the baselines or matches their performance with a simpler architecture and more stable training.
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim
Jiayao Gu
Ye Yuan
Taeyoung Yun
Zixuan Liu
Can Chen
Offline Model-Based Optimization: Comprehensive Review
Minsu Kim
Jiayao Gu
Ye Yuan
Taeyoung Yun
Zixuan Liu
Can Chen
RL4Med-DDPO: Reinforcement Learning for Controlled Guidance Towards Diverse Medical Image Generation using Vision-Language Foundation Models
Parham Saremi
Amar Kumar
Mohammed Mohammed
Zahra Tehraninasab
Meditation induces shifts in neural oscillations, brain complexity and critical dynamics: Novel insights from MEG
Annalisa Pascarella
Philipp Thölke
David Meunier
Jordan O’Byrne
Tarek Lajnef
Antonino Raffone
Roberto Guidotti
Vittorio Pizzella
Laura Marzetti
UI-Vision: A Desktop-centric GUI Benchmark for Visual Perception and Interaction
Shravan Nayak
Xiangru Jian
Kevin Qinghong Lin
Juan A. Rodriguez
Montek Kalsi
Rabiul Awal
M. T. ¨Ozsu
David Vazquez
Perouz Taslakian
Spandana Gella
Sai Rajeswar
Human Annotator
Hitting the right pitch: Cortical tracking of fundamental frequency changes across speech rates in auditory and sensorimotor regions
Yorguin-Jose Mantilla-Ramos
Ana-Sofía Hincapié-Casas
Annalisa Pascarella
Tarek Lajnef
Richard M. Leahy
Emily B.J. Coffey
Véronique Boulenger
Tapered Off-Policy REINFORCE: Stable and efficient reinforcement learning for LLMs
Jonathan Lebensold
Arnaud Bergeron
Joshua Greaves
Alex Fr'echette
Carolyne Pelletier
Eric Thibodeau-Laufer
S'andor Toth
Sam Work