Tootfinder

MAGIC-Enhanced Keyword Prompting for Zero-Shot Audio Captioning with CLIP Models
Vijay Govindarajan, Pratik Patel, Sahil Tripathi, Md Azizul Hoque, Gautam Siddharth Kashyap
https://arxiv.org/abs/2509.12591

MAGIC-Enhanced Keyword Prompting for Zero-Shot Audio Captioning with CLIP Models
Automated Audio Captioning (AAC) generates captions for audio clips but faces challenges due to limited datasets compared to image captioning. To overcome this, we propose the zero-shot AAC system that leverages pre-trained models, eliminating the need for extensive training. Our approach uses a pre-trained audio CLIP model to extract auditory features and generate a structured prompt, which guides a Large Language Model (LLM) in caption generation. Unlike traditional greedy decoding, our metho…

Generalizable Geometric Image Caption Synthesis
Yue Xin, Wenyuan Wang, Rui Pan, Ruida Wang, Howard Meng, Renjie Pi, Shizhe Diao, Tong Zhang
https://arxiv.org/abs/2509.15217 http…

Generalizable Geometric Image Caption Synthesis
Multimodal large language models have various practical applications that demand strong reasoning abilities. Despite recent advancements, these models still struggle to solve complex geometric problems. A key challenge stems from the lack of high-quality image-text pair datasets for understanding geometric images. Furthermore, most template-based data synthesis pipelines typically fail to generalize to questions beyond their predefined templates. In this paper, we bridge this gap by introducing…

Battle Bots

Aligning Audio Captions with Human Preferences
Kartik Hegde, Rehana Mahfuz, Yinyi Guo, Erik Visser
https://arxiv.org/abs/2509.14659 https://arxiv.org/pdf/2…

Aligning Audio Captions with Human Preferences
Current audio captioning systems rely heavily on supervised learning with paired audio-caption datasets, which are expensive to curate and may not reflect human preferences in real-world scenarios. To address this limitation, we propose a preference-aligned audio captioning framework based on Reinforcement Learning from Human Feedback (RLHF). To effectively capture nuanced human preferences, we train a Contrastive Language-Audio Pretraining (CLAP)-based reward model using human-labeled pairwise…

Had an amazing time speaking about Web Design Engineering at @… Freiburg last week! 🎉 It was an honour to be invited and to meet so many wonderful people and good friends there – a truly smashing experience! Thank you, everyone! 🤗💚🎈
📸 Photos by @…

I finished watching this #Netflix documentary about the #Antwerp 🇧🇪 diamond heist in 2003 and while the film itself is your typical interesting and informative Netflix-style docu, I am again peeved that #OpenStreetMap

What's the Best Way to Retrieve Slides? A Comparative Study of Multimodal, Caption-Based, and Hybrid Retrieval Techniques
Petros Stylianos Giouroukis, Dimitris Dimitriadis, Dimitrios Papadopoulos, Zhenwen Shao, Grigorios Tsoumakas
https://arxiv.org/abs/2509.15211

What's the Best Way to Retrieve Slides? A Comparative Study of Multimodal, Caption-Based, and Hybrid Retrieval Techniques
Slide decks, serving as digital reports that bridge the gap between presentation slides and written documents, are a prevalent medium for conveying information in both academic and corporate settings. Their multimodal nature, combining text, images, and charts, presents challenges for retrieval-augmented generation systems, where the quality of retrieval directly impacts downstream performance. Traditional approaches to slide retrieval often involve separate indexing of modalities, which can in…

🇺🇦 Auf radioeins läuft...
Cupidon feat. Milaa:
🎵 Feel It
#NowPlaying #Cupidon #Milaa
https://subreachers.bandcamp.com/track/cupidon-milaa-feel-it-subreachers-jungle-bootleg
https://open.spotify.com/track/5qKEArG4jwMAYTAsuG4rpH

The Call of the Wild
#Sims4 #TheSims4 #Comicstrip

It's funny because when I captioned NPR's audio I realised the transcript on their website is wrong.

David Simon does not say:

"You mentioned that."

He said:

"You imagine that?"

As NPR likely use "AI" for their transcripts, this adds an extra layer of irony.