Multimodal deep learning is a new book published on ArXiv. 4 of 11
@dair_ai
-
OpenAI Research on Generative LM Disinformation Risks
By
–
OpenAI publishes new work analyzing how generative LMs could potentially be misused for disinformation and how to mitigate these types of risks. 5 of 11
-
DeepMind Tracr: Compiler Converting RASP to Transformer Weights
By
–
DeepMind proposes Tracr, a compiler for converting RASP programs into transformer weights. This way of constructing NNs weights enables the development and evaluation of new interpretability tools. 3 of 11
-
Top Machine Learning Papers of the Week
By
–
Top ML Papers of the Week (Jan 9-15): – DreamerV3
– DeepMatcher
– Multimodal deep learning
– Transformer compiler for RASP
– Potential misuses of LMs and mitigations
– Scaling laws for generative mixed-modal LMs
– Time series forecasting with generative modeling
… 1 of 11 -
DreamerV3 Achieves Minecraft Diamond Collection Without Human Data
By
–
DreamerV3 is a general algorithm to collect diamonds in Minecraft from scratch without human data or curricula, a long-standing challenge in AI.
— DAIR.AI (@dair_ai) 15 janvier 2023
2 of 11https://t.co/pvsmnX3TPODreamerV3 is a general algorithm to collect diamonds in Minecraft from scratch without human data or curricula, a long-standing challenge in AI. 2 of 11
-
Comprehensive Prompt Engineering Guide with References
By
–
Prompt Engineering Guide (1.1K) This new guide helps you find the latest & greatest information regarding prompt engineering. More references were added. Lecture + notebook coming soon! https://
github.com/dair-ai/Prompt
-Engineering-Guide
… -
Follow DAIR AI for Trending ML Papers Weekly
By
–
Follow us @dair_ai for upcoming trending ML papers of the week.
-
A Succinct Summary of Reinforcement Learning
By
–
A Succinct Summary of Reinforcement Learning. 11 of 11
-
Integrated Decomposition Improves Science Q&A with Human-in-Loop
By
–
Proposes integrated decomposition, an approach to improve Science Q&A through a human-in-the-loop workflow for refining compositional LM programs. 10 of 11
-
Deep Learning Memorization: Understanding Overfitting Phenomena
By
–
This work aims to better understand how deep learning models overfit or memorize examples; interesting phenomena observed; important work toward a mechanistic theory of memorization. 8 of 11