9 citations · 33 across the 16 of their papers we have counts for
17 papers
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
Shaona Ghosh, Heather Frase, Adina Williams +99
The rapid advancement and deployment of AI systems have created an urgent need for standard safety-evaluation frameworks. This paper introduces AILuminate v1.0, the first comprehen…
Safeguard Fine-Tuned LLMs Through Pre- and Post-Tuning Model Merging
Hua Farn, Hsuan Su, Shachi H Kumar +3
Fine-tuning large language models (LLMs) for downstream tasks often leads to catastrophic forgetting, notably degrading the safety of originally aligned models. While some existing…
Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models
Shachi H Kumar, Saurav Sahay, Sahisnu Mazumder +6
Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are sus…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
Learning from Red Teaming: Gender Bias Provocation and Mitigation in Large Language Models
Hsuan Su, Cheng-Chu Cheng, Hua Farn +4
Recently, researchers have made considerable improvements in dialogue systems with the progress of large language models (LLMs) such as ChatGPT and GPT-4. These LLM-based chatbots…
Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue
Hsuan Su, Shachi H Kumar, Sahisnu Mazumder +7
With the power of large pretrained language models, various research works have integrated knowledge into dialogue systems. The traditional techniques treat knowledge as part of th…
Controllable Response Generation for Assistive Use-cases
Shachi H Kumar, Hsuan Su, Ramesh Manuvinakurike +2
Conversational agents have become an integral part of the general population for simple task enabling situations. However, these systems are yet to have any social impact on the di…
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents
Eda Okur, Shachi H Kumar, Saurav Sahay +1
Building multimodal dialogue understanding capabilities situated in the in-cabin context is crucial to enhance passenger comfort in autonomous vehicle (AV) interaction systems. To…
Low Rank Fusion based Transformers for Multimodal Sequences
Saurav Sahay, Eda Okur, Shachi H Kumar +1
Our senses individually work in a coordinated fashion to express our emotional intentions. In this work, we experiment with modeling modality-specific sensory signals to attend to…
Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
We are witnessing a confluence of vision, speech and dialog system technologies that are enabling the IVAs to learn audio-visual groundings of utterances and have conversations wit…
Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
With the recent advancements in Artificial Intelligence (AI), Intelligent Virtual Assistants (IVA) such as Alexa, Google Home, etc., have become a ubiquitous part of many homes. Cu…
Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions
Saurav Sahay, Shachi H Kumar, Eda Okur +2
Building a machine learning driven spoken dialog system for goal-oriented interactions involves careful design of intents and data collection along with development of intent recog…
Towards Multimodal Understanding of Passenger-Vehicle Interactions in Autonomous Vehicles: Intent/Slot Recognition Utilizing Audio-Visual Data
Eda Okur, Shachi H Kumar, Saurav Sahay +1
Understanding passenger intents from spoken interactions and car's vision (both inside and outside the vehicle) are important building blocks towards developing contextual dialog s…
Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances
Eda Okur, Shachi H Kumar, Saurav Sahay +2
Understanding passenger intents and extracting relevant slots are important building blocks towards developing contextual dialogue systems for natural interactions in autonomous ve…
Context, Attention and Audio Feature Explorations for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +3
With the recent advancements in AI, Intelligent Virtual Assistants (IVA) have become a ubiquitous part of every home. Going forward, we are witnessing a confluence of vision, speec…
Conversational Intent Understanding for Passengers in Autonomous Vehicles
Eda Okur, Shachi H Kumar, Saurav Sahay +2
Understanding passenger intents and extracting relevant slots are important building blocks towards developing a contextual dialogue system responsible for handling certain vehicle…
Multimodal Relational Tensor Network for Sentiment and Emotion Classification
Saurav Sahay, Shachi H Kumar, Rui Xia +2
Understanding Affect from video segments has brought researchers from the language, audio and video domains together. Most of the current multimodal research in this area deals wit…