Search Results for author:
Found 20 papers, 2 papers with code
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Model alignment with human preferences is an essential step in making Large Language Models (LLMs) helpful and consistent with human values.
Retrieval meets Long Context Large Language Models
Perhaps surprisingly, we find that LLM with 4K context window using simple retrieval-augmentation at generation can achieve comparable performance to finetuned LLM with 16K context window via positional interpolation on long context tasks, while taking much less computation.
Duplex Diffusion Models Improve Speech-to-Speech Translation
Speech-to-speech translation is a typical sequence-to-sequence learning task that naturally has two directions.
Enhancing Unsupervised Speech Recognition with Diffusion GANs
We enhance the vanilla adversarial training method for unsupervised Automatic Speech Recognition (ASR) by a diffusion-GAN.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Creative Painting with Latent Diffusion Models
In this paper, we focus on enhancing the creative painting ability of current LDMs in two directions, textual condition extension and model retraining with Wikiart dataset.
Attention Enhanced Citrinet for Speech Recognition
Citrinet is an end-to-end convolutional Connectionist Temporal Classification (CTC) based automatic speech recognition (ASR) model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Deep Sparse Conformer for Speech Recognition
A deep normalization strategy is utilized when performing residual connections to ensure our training of hundred-level Conformer blocks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Machine Reading Comprehension with Enhanced Linguistic Verifiers
We propose two linguistic verifiers for span-extraction style machine reading comprehension to respectively tackle two challenges: how to evaluate the syntactic completeness of predicted answers and how to utilize the rich context of long documents.
Event-Driven Learning of Systematic Behaviours in Stock Markets
It is reported that financial news, especially financial events expressed in news, provide information to investors' long/short decisions and influence the movements of stock markets.
Playing 20 Question Game with Policy-Based Reinforcement Learning
The 20 Questions (Q20) game is a well known game which encourages deductive reasoning and creativity.
Dialog Generation Using Multi-Turn Reasoning Neural Networks
In this paper, we propose a generalizable dialog generation approach that adapts multi-turn reasoning, one recent advancement in the field of document comprehension, to generate responses ({``}answers{''}) by taking current conversation session context as a {``}document{''} and current query as a {``}question{''}.
