Search Results for author:
Found 12 papers, 2 papers with code
Aegis2.0: A Diverse AI Safety Dataset and Risks Taxonomy for Alignment of LLM Guardrails
As Large Language Models (LLMs) and generative AI become increasingly widespread, concerns about content safety have grown in parallel.
Towards Inference-time Category-wise Safety Steering for Large Language Models
While large language models (LLMs) have seen unprecedented advancements in capabilities and applications across a variety of use-cases, safety alignment of these models is still an area of active research.
Nemotron-4 340B Technical Report
We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward.
AEGIS: Online Adaptive AI Content Safety Moderation with Ensemble of LLM Experts
As Large Language Models (LLMs) and generative AI become more widespread, the content safety risks associated with their use also increase.
CantTalkAboutThis: Aligning Language Models to Stay on Topic in Dialogues
Recent advancements in instruction-tuning datasets have predominantly focused on specific tasks like mathematical or logical reasoning.
Joint Learning of Portrait Intrinsic Decomposition and Relighting
To solve this ill-posed problem from single image, state-of-the-art methods in shape from shading mostly resort to supervised training on all the components on either synthetic or real datasets.
Conversational Semantic Parsing for Dialog State Tracking
We consider a new perspective on dialog state tracking (DST), the task of estimating a user's goal through the course of a dialog.
Neuramanteau: A Neural Network Ensemble Model for Lexical Blends
The problem of blend formation in generative linguistics is interesting in the context of neologism, their quick adoption in modern life and the creative generative process guiding their formation.
Neural Networks for Text Correction and Completion in Keyboard Decoding
Our models achieve a word level accuracy of $90\%$ and a character error rate CER of $2. 4\%$ over the Twitter typo dataset.
An Application of Network Lasso Optimization For Ride Sharing Prediction
Ride sharing has important implications in terms of environmental, social and individual goals by reducing carbon footprints, fostering social interactions and economizing commuter costs.
Online Prediction at the Limit of Zero Temperature
We design an online algorithm to classify the vertices of a graph.
Extended Formulations for Online Linear Bandit Optimization
On-line linear optimization on combinatorial action sets (d-dimensional actions) with bandit feedback, is known to have complexity in the order of the dimension of the problem.
