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Found 11 papers, 4 papers with code
SmartFlow: Robotic Process Automation using LLMs
To assess the effectiveness of SmartFlow, we have developed a dataset that includes a set of generic enterprise applications with diverse layouts, which we are releasing for research use.
Multi-Subject Personalization
Creative story illustration requires a consistent interplay of multiple characters or objects.
CustomText: Customized Textual Image Generation using Diffusion Models
Despite recent strides in language-guided image synthesis using diffusion models, current models excel in image generation but struggle with accurate text rendering and offer limited control over font attributes.
Adaptive Exploration for Data-Efficient General Value Function Evaluations
This behavior policy selects actions in proportion to the total variance in the return across all GVFs, reducing the number of environmental interactions.
Towards Painless Policy Optimization for Constrained MDPs
We propose a generic primal-dual framework that allows us to bound the reward sub-optimality and constraint violation for arbitrary algorithms in terms of their primal and dual regret on online linear optimization problems.
TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words
In this paper, we propose to train a deep network to capture the spatial associations between different word pairs present in the table image for unravelling the table structure.
Digitize-PID: Automatic Digitization of Piping and Instrumentation Diagrams
A novel and efficient kernel-based line detection and a two-step method for detection of complex symbols based on a fine-grained deep recognition technique is presented in the paper.
Variance Penalized On-Policy and Off-Policy Actor-Critic
Reinforcement learning algorithms are typically geared towards optimizing the expected return of an agent.
Audrey: A Personalized Open-Domain Conversational Bot
Conversational Intelligence requires that a person engage on informational, personal and relational levels.
Safe Option-Critic: Learning Safety in the Option-Critic Architecture
We propose an optimization objective that learns safe options by encouraging the agent to visit states with higher behavioural consistency.
On Matching Skulls to Digital Face Images: A Preliminary Approach
Forensic application of automatically matching skull with face images is an important research area linking biometrics with practical applications in forensics.
