19 citations · 34 across the 8 of their papers we have counts for
8 papers
A Large Scale Investigation of Scaling Limits in Chemical Language Models
Kamran Chitsaz, Roshan Balaji, Quentin Fournier +2
Chemical Language Models (CLMs) are increasingly used in de novo drug design, driven by recent growth in model scale, compute, and dataset size. However, the relationship between d…
Steering Large Language Model Activations in Sparse Spaces
Reza Bayat, Ali Rahimi-Kalahroudi, Mohammad Pezeshki +2
A key challenge in AI alignment is guiding large language models (LLMs) to follow desired behaviors at test time. Activation steering, which modifies internal model activations dur…
Manifold Metric: A Loss Landscape Approach for Predicting Model Performance
Pranshu Malviya, Jerry Huang, Aristide Baratin +2
Determining the optimal model for a given task often requires training multiple models from scratch, which becomes impractical as dataset and model sizes grow. A more efficient alt…
PatchBlender: A Motion Prior for Video Transformers
Gabriele Prato, Yale Song, Janarthanan Rajendran +3
Transformers have become one of the dominant architectures in the field of computer vision. However, there are yet several challenges when applying such architectures to video data…
An Introduction to Lifelong Supervised Learning
Shagun Sodhani, Mojtaba Faramarzi, Sanket Vaibhav Mehta +4
This primer is an attempt to provide a detailed summary of the different facets of lifelong learning. We start with Chapter 2 which provides a high-level overview of lifelong learn…
Maximum Reward Formulation In Reinforcement Learning
Sai Krishna Gottipati, Yashaswi Pathak, Rohan Nuttall +6
Reinforcement learning (RL) algorithms typically deal with maximizing the expected cumulative return (discounted or undiscounted, finite or infinite horizon). However, several cruc…
GuessWhat?! Visual object discovery through multi-modal dialogue
Harm de Vries, Florian Strub, Sarath Chandar +3
We introduce GuessWhat?!, a two-player guessing game as a testbed for research on the interplay of computer vision and dialogue systems. The goal of the game is to locate an unknow…
Correlational Neural Networks
Sarath Chandar, Mitesh M. Khapra, Hugo Larochelle +1
Common Representation Learning (CRL), wherein different descriptions (or views) of the data are embedded in a common subspace, is receiving a lot of attention recently. Two popular…