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Found 6 papers, 0 papers with code
Neural Slot Interpreters: Grounding Object Semantics in Emergent Slot Representations
Finally, we formulate the NSI program generator model to use the dense associations inferred from the alignment model to generate object-centric programs from slots.
Zero-TPrune: Zero-Shot Token Pruning through Leveraging of the Attention Graph in Pre-Trained Transformers
Deployment of Transformer models on edge devices is becoming increasingly challenging due to the exponentially growing inference cost that scales quadratically with the number of tokens in the input sequence.
SCouT: Synthetic Counterfactuals via Spatiotemporal Transformers for Actionable Healthcare
The Synthetic Control method has pioneered a class of powerful data-driven techniques to estimate the counterfactual reality of a unit from donor units.
FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid?
We also propose a novel NAS policy, called BOSHNAS, that leverages this new scheme, Bayesian modeling, and second-order optimization, to quickly train and use a neural surrogate model to converge to the optimal architecture.
Lower Bounds for Policy Iteration on Multi-action MDPs
An important theoretical question is how many iterations a specified PI variant will take to terminate as a function of the number of states $n$ and the number of actions $k$ in the input MDP.
Analysis of Lower Bounds for Simple Policy Iteration
We generalize the previous result and prove a novel exponential lower bound on the number of iterations taken by policy iteration for $N-$state, $k-$action MDPs.
