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Found 6 papers, 4 papers with code
Simple linear attention language models balance the recall-throughput tradeoff
In this work, we explore whether we can improve language model efficiency (e. g. by reducing memory consumption) without compromising on recall.
Black-Box Access is Insufficient for Rigorous AI Audits
The effectiveness of an audit, however, depends on the degree of system access granted to auditors.
SuperHF: Supervised Iterative Learning from Human Feedback
Here, we focus on two prevalent methods used to align these models, Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).
PIGEON: Predicting Image Geolocations
We train two models for evaluations on street-level data and general-purpose image geolocalization; the first model, PIGEON, is trained on data from the game of Geoguessr and is capable of placing over 40% of its guesses within 25 kilometers of the target location globally.
Ranked #1 on
Photo geolocation estimation
on YFCC4k
Sumformer: Universal Approximation for Efficient Transformers
Natural language processing (NLP) made an impressive jump with the introduction of Transformers.
Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization
Image geolocalization is the challenging task of predicting the geographic coordinates of origin for a given photo.
Ranked #1 on
Photo geolocation estimation
on Im2GPS
(Training images metric)
