On-device research index

arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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13 results for “text-guided”

A Text-guided Protein Design Frameworkcs.LG

A new framework uses text descriptions to improve protein design.

problem Lack of effective methods to incorporate textual descriptions in protein design.

method ProteinDT framework that combines text and protein structural information.

result ProteinDT significantly improves protein design accuracy and performance.

protein design text-guided AI-assisted protein sequence functional description

2023-02-09abs ↗pdf ↗

Zero-Shot Contrastive Loss for Text-Guided Diffusion Image Style Transfercs.CV

Zero-shot contrastive loss improves text-guided image style transfer without extra training.

problem Stochastic nature of diffusion models leads to trade-offs between style transformation and content preservation.

method Proposes a zero-shot contrastive loss for diffusion models that doesn't require additional fine-tuning or auxiliary networks.

result Method outperforms existing methods while preserving content and requiring no additional training.

diffusion models image style transfer zero-shot learning contrastive loss semantic content

2023-03-15abs ↗pdf ↗

Concept Algebra for (Score-Based) Text-Controlled Generative Modelscs.CL

The paper formalizes how concepts are encoded in text-guided generative models and provides a method to manipulate them.

problem Encoding and manipulating concepts in text-guided generative models.

method Formalizing concepts as subspaces of a representation space, developing algebraic manipulation methods.

result The ability to manipulate concepts in generative models through algebraic operations on the representation.

Generative Models Score-Based Models Concepts Disentangled Representation Algebraic Manipulation

2023-02-07abs ↗pdf ↗

Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusioncs.LG

Paper introduces STSL, a second-order Tweedie sampler for efficient posterior sampling in inverse problems.

problem Computational challenges in sampling from posterior distributions using latent diffusion models.

method Introduces STSL, a novel second-order Tweedie sampler with tractable reverse process.

result STSL achieves 4X and 8X reduction in neural function evaluations compared to state-of-the-art solvers.

latent diffusion inverse problems posterior sampling second-order approximation neural function evaluations

2023-12-01abs ↗pdf ↗

ED-NeRF: Efficient Text-Guided Editing of 3D Scene with Latent Space NeRFcs.CV

ED-NeRF efficiently edits 3D scenes using latent space NeRF and improved loss functions.

problem Slow training speeds and inadequate editing loss functions in existing NeRF editing techniques.

method Embedding real-world scenes into latent space of LDM, using a unique refinement layer and an improved loss function.

result ED-NeRF achieves faster editing speed and improved output quality compared to state-of-the-art models.

3D NeRF editing latent space latent diffusion model loss function text-guided editing

2023-10-04abs ↗pdf ↗

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIPcs.LG

CLIP learns joint image-text representations for zero-shot learning.

problem Understanding and improving zero-shot transfer performance in CLIP.

method Formal study of transferrable representation learning and analysis of zero-shot transfer performance.

result Proposes a new CLIP-type approach that outperforms existing methods.

CLIP representation learning zero-shot transfer contrastive pretraining natural image generation

2023-10-02abs ↗pdf ↗

Improving Diffusion-based Image Translation using Asymmetric Gradient Guidancecs.CV

Improved image translation using asymmetric gradient guidance.

problem Trade-off between style transformation and content preservation in diffusion models.

method Asymmetric gradient guidance to guide reverse diffusion sampling.

result Our method outperforms state-of-the-art models in image translation tasks.

image translation diffusion models asymmetric gradient guidance content preservation style transformation

2023-06-07abs ↗pdf ↗

Test-Time Anchoring for Discrete Diffusion Posterior Samplingcs.LG

Discrete diffusion models improve text and image inference.

problem Challenges in posterior sampling with discrete diffusion models.

method Anchored Posterior Sampling (APS) with quantized expectation and anchored remasking.

result APS achieves state-of-the-art performance on various tasks.

discrete diffusion posterior sampling gradient guidance quantization remasking

2025-10-02abs ↗pdf ↗

Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encodersstat.ML

Faster diffusion-based models generate data with fewer steps.

problem Slow and costly diffusion-based generative models.

method Truncate diffusion process to generate data more efficiently.

result Truncated models provide consistent improvements in performance.

diffusion models adversarial auto-encoders generative models data generation noise distribution

2022-02-19abs ↗pdf ↗

Zero-shot Generation of Coherent Storybook from Plain Text Story using Diffusion Modelscs.CV

Generates coherent storybooks from plain text using diffusion models.

problem Ensuring coherency in a sequence of images for storytelling applications.

method Combines pre-trained LLM and text-guided Latent Diffusion Model for zero-shot generation.

result Outperforms state-of-the-art image editing baselines in generating coherent storybooks.

story generation coherent images text-to-image diffusion models zero-shot learning

2023-02-08abs ↗pdf ↗

Diffusion-based Image Translation using Disentangled Style and Content Representationcs.CV

A new method for image translation using disentangled style and content preservation.

problem Difficulty in maintaining original content during reverse diffusion in diffusion-based image translation.

method Disentangled style and content representation using intermediate keys from ViT model, CLIP loss, semantic divergence loss, and resampling strategy.

result Outperforms state-of-the-art models in text-guided and image-guided translation tasks.

image translation disentangled representation semantic divergence CLIP loss reverse diffusion

2022-09-30abs ↗pdf ↗

Spectral-Aware Text-to-Time Series Generation with Billion-Scale Multimodal Meteorological Datacs.LG

Unified framework for generating meteorological time series from text.

problem Lack of large-scale, physically grounded multimodal datasets and architectures ignoring spectral-temporal structure.

method Introduce MeteoCap-3B dataset and MTransformer model.

result State-of-the-art generation quality, accurate cross-modal alignment, strong semantic controllability.

text-to-time series meteorology diffusion model spectral-aware multimodal datasets

2026-03-28abs ↗pdf ↗

Geometry-Complete Diffusion for 3D Molecule Generation and Optimizationcs.LG

GCDM generates valid large 3D molecules and optimizes existing molecules.

problem Lack of geometric properties in 3D molecule generation models.

method Introduces Geometry-Complete Diffusion Model (GCDM) using equivariant GNNs.

result Significantly outperforms existing models in 3D molecule generation and optimization.

3D Molecule Generation Diffusion Models Geometric Properties Equivariant GNNs Molecular Optimization

2023-02-08abs ↗pdf ↗