Tootfinder

Invisible Illusion – Curse Of Knowledge
#abstract

MST-Distill: Mixture of Specialized Teachers for Cross-Modal Knowledge Distillation
Hui Li, Pengfei Yang, Juanyang Chen, Le Dong, Yanxin Chen, Quan Wang
https://arxiv.org/abs/2507.07015

MST-Distill: Mixture of Specialized Teachers for Cross-Modal Knowledge Distillation
Knowledge distillation as an efficient knowledge transfer technique, has achieved remarkable success in unimodal scenarios. However, in cross-modal settings, conventional distillation methods encounter significant challenges due to data and statistical heterogeneities, failing to leverage the complementary prior knowledge embedded in cross-modal teacher models. This paper empirically reveals two critical issues in existing approaches: distillation path selection and knowledge drift. To address …

"What Can We Learn From Open Access Journals in the Arab States?" @ Katina Magazine: https://katinamagazine.org/content/article/open-knowledge/2025/open-access-journals-arab-states
"In the 22 Arab states,

ReservoirChat: Interactive Documentation Enhanced with LLM and Knowledge Graph for ReservoirPy
Virgile Boraud (Mnemosyne), Yannis Bendi-Ouis (Mnemosyne), Paul Bernard (Mnemosyne), Xavier Hinaut (Mnemosyne)
https://arxiv.org/abs/2507.05279

ReservoirChat: Interactive Documentation Enhanced with LLM and Knowledge Graph for ReservoirPy
We introduce a tool designed to improve the capabilities of Large Language Models (LLMs) in assisting with code development using the ReservoirPy library, as well as in answering complex questions in the field of Reservoir Computing. By incorporating external knowledge through Retrieval-Augmented Generation (RAG) and knowledge graphs, our approach aims to reduce hallucinations and increase the factual accuracy of generated responses. The system provides an interactive experience similar to Chat…

Research Awards - 2025 Canadian Friends of Sufi Arts, Culture, and Knowledge (CFSACK) https://networks.h-net.org/group/announcements/20122004/2025-canadian-friends-sufi-arts-culture-and-knowledge-cfsack-research…

Knowledge-Aware Self-Correction in Language Models via Structured Memory Graphs
Swayamjit Saha
https://arxiv.org/abs/2507.04625 https://

Knowledge-Aware Self-Correction in Language Models via Structured Memory Graphs
Large Language Models (LLMs) are powerful yet prone to generating factual errors, commonly referred to as hallucinations. We present a lightweight, interpretable framework for knowledge-aware self-correction of LLM outputs using structured memory graphs based on RDF triples. Without retraining or fine-tuning, our method post-processes model outputs and corrects factual inconsistencies via external semantic memory. We demonstrate the approach using DistilGPT-2 and show promising results on simpl…

ZKTorch: Compiling ML Inference to Zero-Knowledge Proofs via Parallel Proof Accumulation
Bing-Jyue Chen, Lilia Tang, Daniel Kang
https://arxiv.org/abs/2507.07031

ZKTorch: Compiling ML Inference to Zero-Knowledge Proofs via Parallel Proof Accumulation
As AI models become ubiquitous in our daily lives, there has been an increasing demand for transparency in ML services. However, the model owner does not want to reveal the weights, as they are considered trade secrets. To solve this problem, researchers have turned to zero-knowledge proofs of ML model inference. These proofs convince the user that the ML model output is correct, without revealing the weights of the model to the user. Past work on these provers can be placed into two categories…

"We need to avail ourselves of GenAI to enhance knowledge distribution": Empowering Older Adults through GenAI Literacy
Eunhye Grace Ko, Shaini Nanayakkara, Earl W. Huff Jr
https://arxiv.org/abs/2506.06225

"We need to avail ourselves of GenAI to enhance knowledge distribution": Empowering Older Adults through GenAI Literacy
As generative AI (GenAI) becomes increasingly widespread, it is crucial to equip users, particularly vulnerable populations such as older adults (65 and older), with the knowledge to understand its benefits and potential risks. Older adults often exhibit greater reservations about adopting emerging technologies and require tailored literacy support. Using a mixed methods approach, this study examines strategies for delivering GenAI literacy to older adults through a chatbot named Litti, evaluat…

Enhancing Food-Domain Question Answering with a Multimodal Knowledge Graph: Hybrid QA Generation and Diversity Analysis
Srihari K B, Pushpak Bhattacharyya
https://arxiv.org/abs/2507.06571

Enhancing Food-Domain Question Answering with a Multimodal Knowledge Graph: Hybrid QA Generation and Diversity Analysis
We propose a unified food-domain QA framework that combines a large-scale multimodal knowledge graph (MMKG) with generative AI. Our MMKG links 13,000 recipes, 3,000 ingredients, 140,000 relations, and 14,000 images. We generate 40,000 QA pairs using 40 templates and LLaVA/DeepSeek augmentation. Joint fine-tuning of Meta LLaMA 3.1-8B and Stable Diffusion 3.5-Large improves BERTScore by 16.2\%, reduces FID by 37.8\%, and boosts CLIP alignment by 31.1\%. Diagnostic analyses-CLIP-based mismatch det…

zkSDK: Streamlining zero-knowledge proof development through automated trace-driven ZK-backend selection
William Law
https://arxiv.org/abs/2507.05294 https…

zkSDK: Streamlining zero-knowledge proof development through automated trace-driven ZK-backend selection
The rapid advancement of creating Zero-Knowledge (ZK) programs has led to the development of numerous tools designed to support developers. Popular options include being able to write in general-purpose programming languages like Rust from Risc Zero. Other languages exist like Circom, Lib-snark, and Cairo. However, developers entering the ZK space are faced with many different ZK backends to choose from, leading to a steep learning curve and a fragmented developer experience across different pl…