333 citations · 588 across the 48 of their papers we have counts for
6 papers · 1 filter
TangoFlux: Super Fast and Faithful Text to Audio Generation with Flow Matching and Clap-Ranked Preference Optimization
Chia-Yu Hung, Navonil Majumder, Zhifeng Kong +6
We introduce TangoFlux, an efficient Text-to-Audio (TTA) generative model with 515M parameters, capable of generating up to 30 seconds of 44.1kHz audio in just 3.7 seconds on a sin…
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Maojia Song, Shang Hong Sim, Rishabh Bhardwaj +3
LLMs are an integral component of retrieval-augmented generation (RAG) systems. While many studies focus on evaluating the overall quality of end-to-end RAG systems, there is a gap…
Improving Text-To-Audio Models with Synthetic Captions
Zhifeng Kong, Sang-gil Lee, Deepanway Ghosal +5
It is an open challenge to obtain high quality training data, especially captions, for text-to-audio models. Although prior methods have leveraged \textit{text-only language models…
Inference Time Alignment with Reward-Guided Tree Search
Chia-Yu Hung, Navonil Majumder, Ambuj Mehrish +1
Inference-time computation methods enhance the performance of Large Language Models (LLMs) by leveraging additional computational resources to achieve superior results. Common tech…
Tango 2: Aligning Diffusion-based Text-to-Audio Generations through Direct Preference Optimization
Navonil Majumder, Chia-Yu Hung, Deepanway Ghosal +3
Generative multimodal content is increasingly prevalent in much of the content creation arena, as it has the potential to allow artists and media personnel to create pre-production…
Evaluating LLMs' Mathematical and Coding Competency through Ontology-guided Interventions
Pengfei Hong, Navonil Majumder, Deepanway Ghosal +3
Recent advancements in Large Language Models (LLMs) have showcased striking results on existing logical reasoning benchmarks, with some models even surpassing human performance. Ho…