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Example: Consider that BibTeX entry: @inproceedings{li-etal-2025-instructany2pix, title = "{I}nstruct{A}ny2{P}ix: Image Editing with Multi-Modal Prompts", author = "Li, Shufan and ...
#2: Post edited
by
Franck Dernoncourt
·
2025-05-11T21:41:46Z (4 days ago)
- Example:
- Consider that BibTeX entry:
- ```
- @inproceedings{li-etal-2025-instructany2pix,
- title = "{I}nstruct{A}ny2{P}ix: Image Editing with Multi-Modal Prompts",
- author = "Li, Shufan and
- Singh, Harkanwar and
- Grover, Aditya",
- editor = "Chiruzzo, Luis and
- Ritter, Alan and
- Wang, Lu",
- booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
- month = apr,
- year = "2025",
- address = "Albuquerque, New Mexico",
- publisher = "Association for Computational Linguistics",
- url = "https://aclanthology.org/2025.findings-naacl.36/",
- pages = "594--619",
- ISBN = "979-8-89176-195-7",
- abstract = "Image Editing has made incredible progress in recent years. Earliest work only supported caption-guided editing. Recently, free-form text instructions and reference images are incorporated to allow more flexibility. However, existing methods still struggle with complicated editing instructions involving multiple objects or reference images. We present InstructAny2Pix, a novel image editing model that leverages a multi-modal LLM to execute complicated edit instructions. Compared with previous, works, InstructAny2Pix extends the flexibility of edit instructions in three ways: First, it can perform complex instructions involving multiple object edits; Second, it supports interleaving text instructions with multiple reference images; Third, it supports audio and music inputs as part of edit prompts, unlocking many creative applications, such as album cover generation and music-inspired merchandise design. To evaluate the effectiveness of InstructAny2Pix, we propose two new benchmark datasets MM-Inst and Dream-booth++ consisting of human written, multi-modal prompts. InstructAny2Pix outperforms baselines in these two proposed multi-modal benchmarks, as well as conventional image editing benchmarks such as InstructPix2Pix."
- }
- ```
Is it preferable write `{I}nstruct{A}ny2{P}ix` or `{InstructAny2Pix}`, or that makes no difference?
- Example:
- Consider that BibTeX entry:
- ```
- @inproceedings{li-etal-2025-instructany2pix,
- title = "{I}nstruct{A}ny2{P}ix: Image Editing with Multi-Modal Prompts",
- author = "Li, Shufan and
- Singh, Harkanwar and
- Grover, Aditya",
- editor = "Chiruzzo, Luis and
- Ritter, Alan and
- Wang, Lu",
- booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
- month = apr,
- year = "2025",
- address = "Albuquerque, New Mexico",
- publisher = "Association for Computational Linguistics",
- url = "https://aclanthology.org/2025.findings-naacl.36/",
- pages = "594--619",
- ISBN = "979-8-89176-195-7",
- abstract = "Image Editing has made incredible progress in recent years. Earliest work only supported caption-guided editing. Recently, free-form text instructions and reference images are incorporated to allow more flexibility. However, existing methods still struggle with complicated editing instructions involving multiple objects or reference images. We present InstructAny2Pix, a novel image editing model that leverages a multi-modal LLM to execute complicated edit instructions. Compared with previous, works, InstructAny2Pix extends the flexibility of edit instructions in three ways: First, it can perform complex instructions involving multiple object edits; Second, it supports interleaving text instructions with multiple reference images; Third, it supports audio and music inputs as part of edit prompts, unlocking many creative applications, such as album cover generation and music-inspired merchandise design. To evaluate the effectiveness of InstructAny2Pix, we propose two new benchmark datasets MM-Inst and Dream-booth++ consisting of human written, multi-modal prompts. InstructAny2Pix outperforms baselines in these two proposed multi-modal benchmarks, as well as conventional image editing benchmarks such as InstructPix2Pix."
- }
- ```
- Is it preferable write `{I}nstruct{A}ny2{P}ix` or `{InstructAny2Pix}`, or that makes no difference?
- ----
- Crossposts:
- - https://redd.it/1kkc5d4
- - https://qr.ae/pAbxjN
- - https://tex.stackexchange.com/q/742461/11400
#1: Initial revision
by
Franck Dernoncourt
·
2025-05-11T21:39:30Z (4 days ago)
In the title of a BibTeX entry, is it preferable to write {W}ord{S}tyle or {WordStyle}, or does it make no difference?
Example:
Consider that BibTeX entry:
```
@inproceedings{li-etal-2025-instructany2pix,
title = "{I}nstruct{A}ny2{P}ix: Image Editing with Multi-Modal Prompts",
author = "Li, Shufan and
Singh, Harkanwar and
Grover, Aditya",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: NAACL 2025",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.findings-naacl.36/",
pages = "594--619",
ISBN = "979-8-89176-195-7",
abstract = "Image Editing has made incredible progress in recent years. Earliest work only supported caption-guided editing. Recently, free-form text instructions and reference images are incorporated to allow more flexibility. However, existing methods still struggle with complicated editing instructions involving multiple objects or reference images. We present InstructAny2Pix, a novel image editing model that leverages a multi-modal LLM to execute complicated edit instructions. Compared with previous, works, InstructAny2Pix extends the flexibility of edit instructions in three ways: First, it can perform complex instructions involving multiple object edits; Second, it supports interleaving text instructions with multiple reference images; Third, it supports audio and music inputs as part of edit prompts, unlocking many creative applications, such as album cover generation and music-inspired merchandise design. To evaluate the effectiveness of InstructAny2Pix, we propose two new benchmark datasets MM-Inst and Dream-booth++ consisting of human written, multi-modal prompts. InstructAny2Pix outperforms baselines in these two proposed multi-modal benchmarks, as well as conventional image editing benchmarks such as InstructPix2Pix."
}
```
Is it preferable write `{I}nstruct{A}ny2{P}ix` or `{InstructAny2Pix}`, or that makes no difference?