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Found 8 papers, 7 papers with code
Large-Scale Data Selection for Instruction Tuning
However, popular deployed instruction-tuned models often train on hundreds of thousands to millions of samples, subsampled from even larger data pools.
Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping
Our insight is that in addition to systems optimization, one can also redesign the model architecture to decouple communication from computation.
Learning to Build by Building Your Own Instructions
By disassembling an unseen assembly and periodically saving images of it, the agent is able to create a set of instructions so that it has the information necessary to rebuild it.
Toward a More Complete OMR Solution
One approach to tackle OMR is through a multi-stage pipeline, where the system first detects visual music notation elements in the image (object detection) and then assembles them into a music notation (notation assembly).
STOW: Discrete-Frame Segmentation and Tracking of Unseen Objects for Warehouse Picking Robots
Segmentation and tracking of unseen object instances in discrete frames pose a significant challenge in dynamic industrial robotic contexts, such as distribution warehouses.
How Language Model Hallucinations Can Snowball
A major risk of using language models in practical applications is their tendency to hallucinate incorrect statements.
Measuring and Narrowing the Compositionality Gap in Language Models
We investigate the ability of language models to perform compositional reasoning tasks where the overall solution depends on correctly composing the answers to sub-problems.
Ranked #2 on
Question Answering
on FEVER
Break and Make: Interactive Structural Understanding Using LEGO Bricks
We pair this simulator with a new dataset of fan-made LEGO creations that have been uploaded to the internet in order to provide complex scenes containing over a thousand unique brick shapes.
