Search Results for author:
Found 17 papers, 8 papers with code
Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving
The task of issue resolving is to modify a codebase to generate a patch that addresses a given issue.
MoonCast: High-Quality Zero-Shot Podcast Generation
Recent advances in text-to-speech synthesis have achieved notable success in generating high-quality short utterances for individual speakers.
The Best of Both Worlds: Integrating Language Models and Diffusion Models for Video Generation
Recent advancements in text-to-video (T2V) generation have been driven by two competing paradigms: autoregressive language models and diffusion models.
BFS-Prover: Scalable Best-First Tree Search for LLM-based Automatic Theorem Proving
In this paper, we investigate whether BFS can achieve competitive performance in large-scale theorem proving tasks.
FullStack Bench: Evaluating LLMs as Full Stack Coders
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing.
Ask Questions with Double Hints: Visual Question Generation with Answer-awareness and Region-reference
The visual question generation (VQG) task aims to generate human-like questions from an image and potentially other side information (e. g. answer type).
T2S-GPT: Dynamic Vector Quantization for Autoregressive Sign Language Production from Text
In this work, we propose a two-stage sign language production (SLP) paradigm that first encodes sign language sequences into discrete codes and then autoregressively generates sign language from text based on the learned codebook.
RALL-E: Robust Codec Language Modeling with Chain-of-Thought Prompting for Text-to-Speech Synthesis
Furthermore, we demonstrate that RALL-E correctly synthesizes sentences that are hard for VALL-E and reduces the error rate from $68\%$ to $4\%$.
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Specifically, 1) we design a neural codec with factorized vector quantization (FVQ) to disentangle speech waveform into subspaces of content, prosody, timbre, and acoustic details; 2) we propose a factorized diffusion model to generate attributes in each subspace following its corresponding prompt.
PromptTTS 2: Describing and Generating Voices with Text Prompt
TTS approaches based on the text prompt face two main challenges: 1) the one-to-many problem, where not all details about voice variability can be described in the text prompt, and 2) the limited availability of text prompt datasets, where vendors and large cost of data labeling are required to write text prompts for speech.
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
To enhance the zero-shot capability that is important to achieve diverse speech synthesis, we design a speech prompting mechanism to facilitate in-context learning in the diffusion model and the duration/pitch predictor.
Deep Learning Predicts Prevalent and Incident Parkinson's Disease From UK Biobank Fundus Imaging
Parkinson's disease is the world's fastest-growing neurological disorder.
A Study on ReLU and Softmax in Transformer
This paper sheds light on the following points: 1) Softmax and ReLU use different normalization methods over elements which lead to different variances of results, and ReLU is good at dealing with a large number of key-value slots; 2) FFN and key-value memory are equivalent, and thus the Transformer can be viewed as a memory network where FFNs and self-attention networks are both key-value memories.
Mask the Correct Tokens: An Embarrassingly Simple Approach for Error Correction
Since the error rate of the incorrect sentence is usually low (e. g., 10\%), the correction model can only learn to correct on limited error tokens but trivially copy on most tokens (correct tokens), which harms the effective training of error correction.
Scenario-based Multi-product Advertising Copywriting Generation for E-Commerce
In this paper, we proposed an automatic Scenario-based Multi-product Advertising Copywriting Generation system (SMPACG) for E-Commerce, which has been deployed on a leading Chinese e-commerce platform.
Graph Neural Networks for Natural Language Processing: A Survey
Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).
Fault Detection Using Nonlinear Low-Dimensional Representation of Sensor Data
Sensor data analysis plays a key role in health assessment of critical equipment.
