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Found 8 papers, 4 papers with code
The Wisdom of Hindsight Makes Language Models Better Instruction Followers
In this paper, we consider an alternative approach: converting feedback to instruction by relabeling the original one and training the model for better alignment in a supervised manner.
Context-Aware Streaming Perception in Dynamic Environments
These works evaluate accuracy offline, one image at a time.
Addressing the IEEE AV Test Challenge with Scenic and VerifAI
Sampling from an abstract scenario yields many different concrete scenarios which can be run as test cases for the AV.
Scaled-Time-Attention Robust Edge Network
We demonstrate that STARE is applicable to a variety of applications with improved performance and lower implementation complexity.
A Meta Learning Approach to Discerning Causal Graph Structure
This methodology demonstrates ability to infer the existence as well as the direction of a causal relationship between data distributions.
Learning Nonlinear Loop Invariants with Gated Continuous Logic Networks (Extended Version)
In this paper, we introduce a new neural architecture for general SMT learning, the Gated Continuous Logic Network (G-CLN), and apply it to nonlinear loop invariant learning.
CLN2INV: Learning Loop Invariants with Continuous Logic Networks
We use CLNs to implement a new inference system for loop invariants, CLN2INV, that significantly outperforms existing approaches on the popular Code2Inv dataset.
A Neuro-Fuzzy Method to Improving Backfiring Conversion Ratios
This study introduces a method to improve the accuracy of backfiring.
