Angle-optimized text embeddings
High-quality text embedding is pivotal in improving semantic textual similarity (STS) tasks,
which are crucial components in Large Language Model (LLM) applications. However, a …
which are crucial components in Large Language Model (LLM) applications. However, a …
Animatabledreamer: Text-guided non-rigid 3d model generation and reconstruction with canonical score distillation
Advances in 3D generation have facilitated sequential 3D model generation (aka 4D
generation), yet its application for animatable objects with large motion remains scarce. Our …
generation), yet its application for animatable objects with large motion remains scarce. Our …
AoE: Angle-optimized embeddings for semantic textual similarity
Text embedding is pivotal in semantic textual similarity (STS) tasks, which are crucial
components in Large Language Model (LLM) applications. STS learning largely relies on …
components in Large Language Model (LLM) applications. STS learning largely relies on …
Vividdreamer: invariant score distillation for hyper-realistic text-to-3d generation
Abstract This paper presents Invariant Score Distillation (ISD), a novel method for high-
fidelity text-to-3D generation. ISD aims to tackle the over-saturation and over-smoothing …
fidelity text-to-3D generation. ISD aims to tackle the over-saturation and over-smoothing …
Mind-3D: reconstruct high-quality 3D objects in human brain
In this paper, we introduce Recon3DMind, an innovative task aimed at reconstructing 3D
visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant …
visuals from Functional Magnetic Resonance Imaging (fMRI) signals, marking a significant …
Automatic smart contract comment generation via large language models and in-context learning
Context: Designing effective automatic smart contract comment generation approaches can
facilitate developers' comprehension, boosting smart contract development and improving …
facilitate developers' comprehension, boosting smart contract development and improving …
2d matryoshka sentence embeddings
Common approaches rely on fixed-length embedding vectors from language models as
sentence embeddings for downstream tasks such as semantic textual similarity (STS). Such …
sentence embeddings for downstream tasks such as semantic textual similarity (STS). Such …
DeeLM: Dependency-enhanced Large Language Model for Sentence Embeddings
Recent studies have proposed using large language models (LLMs) for sentence
embeddings. However, most existing LLMs are built with an autoregressive architecture that …
embeddings. However, most existing LLMs are built with an autoregressive architecture that …
When Text Embedding Meets Large Language Model: A Comprehensive Survey
Text embedding has become a foundational technology in natural language processing
(NLP) during the deep learning era, driving advancements across a wide array of …
(NLP) during the deep learning era, driving advancements across a wide array of …
BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings
Sentence embeddings are crucial in measuring semantic similarity. Most recent studies
employed large language models (LLMs) to learn sentence embeddings. Existing LLMs …
employed large language models (LLMs) to learn sentence embeddings. Existing LLMs …