Search Results for author:
Found 15 papers, 7 papers with code
Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
Parameter Efficient Fine-Tuning (PEFT) methods have been extensively utilized in Large Language Models (LLMs) to improve the down-streaming tasks without the cost of fine-tuing the whole LLMs.
ToolNet: Connecting Large Language Models with Massive Tools via Tool Graph
While achieving remarkable progress in a broad range of tasks, large language models (LLMs) remain significantly limited in properly using massive external tools.
CLAPSep: Leveraging Contrastive Pre-trained Models for Multi-Modal Query-Conditioned Target Sound Extraction
Such systems consist of two components: a query network that converts user queries into conditional embeddings, and a separation network that extracts the target sound based on conditional embeddings.
Ranked #1 on
Target Sound Extraction
on AudioSet
FNSPID: A Comprehensive Financial News Dataset in Time Series
Financial market predictions utilize historical data to anticipate future stock prices and market trends.
Explainable Trajectory Representation through Dictionary Learning
A hierarchical dictionary learning scheme is also proposed to ensure the algorithm's scalability on large networks, leading to a multi-scale trajectory representation.
Extending Whisper with prompt tuning to target-speaker ASR
Target-speaker automatic speech recognition (ASR) aims to transcribe the desired speech of a target speaker from multi-talker overlapped utterances.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
CoMFLP: Correlation Measure based Fast Search on ASR Layer Pruning
The search process is carried out in two steps: (1) coarse search: to determine top $K$ candidates by pruning the most redundant layers based on the correlation matrix; (2) fine search: to select the best pruning proposal among $K$ candidates using a task-specific evaluation metric.
Sparsely Shared LoRA on Whisper for Child Speech Recognition
Child speech, as a representative type of low-resource speech, is leveraged for adaptation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Gentopia: A Collaborative Platform for Tool-Augmented LLMs
We present gentopia, an ALM framework enabling flexible customization of agents through simple configurations, seamlessly integrating various language models, task formats, prompting modules, and plugins into a unified paradigm.
ReWOO: Decoupling Reasoning from Observations for Efficient Augmented Language Models
Augmented Language Models (ALMs) blend the reasoning capabilities of Large Language Models (LLMs) with tools that allow for knowledge retrieval and action execution.
DIANES: A DEI Audit Toolkit for News Sources
Professional news media organizations have always touted the importance that they give to multiple perspectives.
Exploiting Pre-Trained ASR Models for Alzheimer's Disease Recognition Through Spontaneous Speech
Input to these classifiers are speech transcripts produced by automatic speech recognition (ASR) models.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Mixture factorized auto-encoder for unsupervised hierarchical deep factorization of speech signal
The USM experiments on ZeroSpeech 2017 dataset verify that the frame tokenizer is able to capture linguistic content and the utterance embedder can acquire speaker-related information.
Combining Adversarial Training and Disentangled Speech Representation for Robust Zero-Resource Subword Modeling
Experimental results on ZeroSpeech 2017 show that both approaches are effective while the latter is more prominent, and that their combination brings further marginal improvement in across-speaker condition.
