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Found 18 papers, 10 papers with code
Adaptive Deadlock Avoidance for Decentralized Multi-agent Systems via CBF-inspired Risk Measurement
To avoid dominating effects due to the deadlock resolution over the original task-related controllers, a deadlock indicator function using CBF-inspired risk measurement is proposed and encoded in the unified framework for the agents to adaptively determine when to activate the deadlock resolution.
Super-resolution of biomedical volumes with 2D supervision
Volumetric biomedical microscopy has the potential to increase the diagnostic information extracted from clinical tissue specimens and improve the diagnostic accuracy of both human pathologists and computational pathology models.
Step-Calibrated Diffusion for Biomedical Optical Image Restoration
Here, we present Restorative Step-Calibrated Diffusion (RSCD), an unpaired diffusion-based image restoration method that uses a step calibrator model to dynamically determine the number of steps required to complete the reverse diffusion process for image restoration.
A self-supervised framework for learning whole slide representations
Whole slide imaging is fundamental to biomedical microscopy and computational pathology.
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues
Our TOD-Flow graph learns what a model can, should, and should not predict, effectively reducing the search space and providing a rationale for the model's prediction.
Code Models are Zero-shot Precondition Reasoners
One of the fundamental skills required for an agent acting in an environment to complete tasks is the ability to understand what actions are plausible at any given point.
MultiZoo & MultiBench: A Standardized Toolkit for Multimodal Deep Learning
Learning multimodal representations involves integrating information from multiple heterogeneous sources of data.
Fine-grained Text Style Transfer with Diffusion-Based Language Models
Diffusion probabilistic models have shown great success in generating high-quality images controllably, and researchers have tried to utilize this controllability into text generation domain.
Risk-aware Safe Control for Decentralized Multi-agent Systems via Dynamic Responsibility Allocation
Decentralized control schemes are increasingly favored in various domains that involve multi-agent systems due to the need for computational efficiency as well as general applicability to large-scale systems.
Model-based Dynamic Shielding for Safe and Efficient Multi-Agent Reinforcement Learning
This design enables efficient synthesis of shields to monitor agents in complex environments without coordination overheads.
Multi-agent Reinforcement Learning
reinforcement-learning
+2
Safe Reinforcement Learning with Probabilistic Control Barrier Functions for Ramp Merging
We use probabilistic control barrier functions as an estimate of the model uncertainty.
Nano: Nested Human-in-the-Loop Reward Learning for Few-shot Language Model Control
Existing techniques for controlling the distribution of generated text only work with quantified distributions, which require pre-defined categories, proportions of the distribution, or an existing corpus following the desired distributions.
MultiViz: Towards Visualizing and Understanding Multimodal Models
How can we visualize the internal modeling of multimodal interactions in these models?
DIME: Fine-grained Interpretations of Multimodal Models via Disentangled Local Explanations
The ability for a human to understand an Artificial Intelligence (AI) model's decision-making process is critical in enabling stakeholders to visualize model behavior, perform model debugging, promote trust in AI models, and assist in collaborative human-AI decision-making.
High-Modality Multimodal Transformer: Quantifying Modality & Interaction Heterogeneity for High-Modality Representation Learning
Many real-world problems are inherently multimodal, from spoken language, gestures, and paralinguistics humans use to communicate, to force, proprioception, and visual sensors on robots.
MultiBench: Multiscale Benchmarks for Multimodal Representation Learning
In order to accelerate progress towards understudied modalities and tasks while ensuring real-world robustness, we release MultiBench, a systematic and unified large-scale benchmark spanning 15 datasets, 10 modalities, 20 prediction tasks, and 6 research areas.
StylePTB: A Compositional Benchmark for Fine-grained Controllable Text Style Transfer
Many of the existing style transfer benchmarks primarily focus on individual high-level semantic changes (e. g. positive to negative), which enable controllability at a high level but do not offer fine-grained control involving sentence structure, emphasis, and content of the sentence.
The State and Future of Genetic Improvement
We report the discussion session at the sixth international Genetic Improvement workshop, GI-2019 @ ICSE, which was held as part of the 41st ACM/IEEE International Conference on Software Engineering on Tuesday 28th May 2019.
