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Found 16 papers, 3 papers with code
Image Classifier Based Generative Method for Planar Antenna Design
To extend the antenna design on printed circuit boards (PCBs) for more engineers of interest, we propose a simple method that models PCB antennas with a few basic components.
The ART of LLM Refinement: Ask, Refine, and Trust
In recent years, Large Language Models (LLMs) have demonstrated remarkable generative abilities, but can they judge the quality of their own generations?
Ranked #12 on
Arithmetic Reasoning
on GSM8K
End-to-end Story Plot Generator
Story plots, while short, carry most of the essential information of a full story that may contain tens of thousands of words.
Learning Personalized Story Evaluation
We further develop a personalized story evaluation model PERSE to infer reviewer preferences and provide a personalized evaluation.
Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decoding
The key idea is not to throw out the value network, a byproduct of PPO training for evaluating partial output sequences, when decoding text out of the policy network.
Sample-efficient Surrogate Model for Frequency Response of Linear PDEs using Self-Attentive Complex Polynomials
Linear Partial Differential Equations (PDEs) govern the spatial-temporal dynamics of physical systems that are essential to building modern technology.
Biomedical image analysis competitions: The state of current participation practice
Of these, 84% were based on standard architectures.
Transfer RL across Observation Feature Spaces via Model-Based Regularization
In many reinforcement learning (RL) applications, the observation space is specified by human developers and restricted by physical realizations, and may thus be subject to dramatic changes over time (e. g. increased number of observable features).
On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning
In this work, we first demonstrate that sample complexity increases with the quantity of absorbing states in a toy supervised learning task for a fully connected network, while attention is more robust to variable size input.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Generating Multi-type Temporal Sequences to Mitigate Class-imbalanced Problem
From the ad network standpoint, a user's activity is a multi-type sequence of temporal events consisting of event types and time intervals.
Perfecting the Crime Machine
We use different techniques to extract various features including combining unsupervised learning techniques and try to predict the crime type.
Maximum Entropy Diverse Exploration: Disentangling Maximum Entropy Reinforcement Learning
A theoretical investigation shows that the set of policies learned by MEDE capture the same modalities as the optimal maximum entropy policy.
Diverse Exploration via Conjugate Policies for Policy Gradient Methods
We address the challenge of effective exploration while maintaining good performance in policy gradient methods.
Unity: A General Platform for Intelligent Agents
Recent advances in artificial intelligence have been driven by the presence of increasingly realistic and complex simulated environments.
Diverse Exploration for Fast and Safe Policy Improvement
We study an important yet under-addressed problem of quickly and safely improving policies in online reinforcement learning domains.
GRIFT: A graphical model for inferring visual classification features from human data
This paper describes a new model for human visual classification that enables the recovery of image features that explain human subjects' performance on different visual classification tasks.
