Tootfinder

Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models
Zahra Babaiee, Peyman M. Kiasari, Daniela Rus, Radu Grosu
https://arxiv.org/abs/2506.06242

Visual Graph Arena: Evaluating Visual Conceptualization of Vision and Multimodal Large Language Models
Recent advancements in multimodal large language models have driven breakthroughs in visual question answering. Yet, a critical gap persists, `conceptualization'-the ability to recognize and reason about the same concept despite variations in visual form, a basic ability of human reasoning. To address this challenge, we introduce the Visual Graph Arena (VGA), a dataset featuring six graph-based tasks designed to evaluate and improve AI systems' capacity for visual abstraction. VGA uses diverse …

Sentinel: SOTA model to protect against prompt injections
Dror Ivry, Oran Nahum
https://arxiv.org/abs/2506.05446 https://arxiv.org/pd…

Sentinel: SOTA model to protect against prompt injections
Large Language Models (LLMs) are increasingly powerful but remain vulnerable to prompt injection attacks, where malicious inputs cause the model to deviate from its intended instructions. This paper introduces Sentinel, a novel detection model, qualifire/prompt-injection-sentinel, based on the \answerdotai/ModernBERT-large architecture. By leveraging ModernBERT's advanced features and fine-tuning on an extensive and diverse dataset comprising a few open-source and private collections, Sentinel …

The State-of-the-Art in Lifelog Retrieval: A Review of Progress at the ACM Lifelog Search Challenge Workshop 2022-24
Allie Tran, Werner Bailer, Duc-Tien Dang-Nguyen, Graham Healy, Steve Hodges, Bj\"orn {\TH}\'or J\'onsson, Luca Rossetto, Klaus Schoeffmann, Minh-Triet Tran, Lucia Vadicamo, Cathal Gurrin
https://arxiv…

The State-of-the-Art in Lifelog Retrieval: A Review of Progress at the ACM Lifelog Search Challenge Workshop 2022-24
The ACM Lifelog Search Challenge (LSC) is a venue that welcomes and compares systems that support the exploration of lifelog data, and in particular the retrieval of specific information, through an interactive competition format. This paper reviews the recent advances in interactive lifelog retrieval as demonstrated at the ACM LSC from 2022 to 2024. Through a detailed comparative analysis, we highlight key improvements across three main retrieval tasks: known-item search, question answering, a…

#StarTrek without computers is inconceivable. Which makes advancements in computer science an important milestone; and also the subject of today's #TrekTriviaTuesday question.
As always no googling and no spoiling the answer for others. Please boost after voting! :BoostOK:
Vote…

On the Comprehensibility of Multi-structured Financial Documents using LLMs and Pre-processing Tools
Shivani Upadhyay, Messiah Ataey, Shariyar Murtuza, Yifan Nie, Jimmy Lin
https://arxiv.org/abs/2506.05182

On the Comprehensibility of Multi-structured Financial Documents using LLMs and Pre-processing Tools
The proliferation of complex structured data in hybrid sources, such as PDF documents and web pages, presents unique challenges for current Large Language Models (LLMs) and Multi-modal Large Language Models (MLLMs) in providing accurate answers. Despite the recent advancements of MLLMs, they still often falter when interpreting intricately structured information, such as nested tables and multi-dimensional plots, leading to hallucinations and erroneous outputs. This paper explores the capabilit…

Cascadia: A Cascade Serving System for Large Language Models
Youhe Jiang, Fangcheng Fu, Wanru Zhao, Stephan Rabanser, Nicholas D. Lane, Binhang Yuan
https://arxiv.org/abs/2506.04203

Cascadia: A Cascade Serving System for Large Language Models
Recent advances in large language models (LLMs) have intensified the need to deliver both rapid responses and high-quality answers. More powerful models yield better results but incur higher inference latency, whereas smaller models are faster yet less capable. Recent work proposes balancing this latency-quality trade-off using model cascades, which route simpler queries to smaller models and more complex ones to larger models. However, enabling efficient cascade serving remains challenging. Cu…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho
https://arxiv.org/abs/2506.00781 ht…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Recent advances in Large Language Models (LLMs) have spurred transformative applications in various domains, ranging from open-source to proprietary LLMs. However, jailbreak attacks, which aim to break safety alignment and user compliance by tricking the target LLMs into answering harmful and risky responses, are becoming an urgent concern. The practice of red-teaming for LLMs is to proactively explore potential risks and error-prone instances before the release of frontier AI technology. This …

This https://arxiv.org/abs/2505.24718 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Reinforcing Video Reasoning with Focused Thinking
Recent advancements in reinforcement learning, particularly through Group Relative Policy Optimization (GRPO), have significantly improved multimodal large language models for complex reasoning tasks. However, two critical limitations persist: 1) they often produce unfocused, verbose reasoning chains that obscure salient spatiotemporal cues and 2) binary rewarding fails to account for partially correct answers, resulting in high reward variance and inefficient learning. In this paper, we propos…

Ultrasonic spin pumping in the antiferromagnetic acoustic resonator $\alpha-\text{Fe}_2\text{O}_3$
David A. Gabrielyan, Dmitry A. Volkov, Tatyana V. Bogdanova, Kristina D. Samoylenko, Anton V. Matasov, Ansar R. Safin, Dmitry V. Kalyabin, Alexey A. Klimov, Leonid M. Krutyansky, Vladimir L. Preobrazhensky, Sergey A. Nikitov
https://

Ultrasonic spin pumping in the antiferromagnetic acoustic resonator $α-\text{Fe}_2\text{O}_3$
Recent advances in magnon spintronics have ignited interest in the interactions between the spin and elastic subsystems of magnetic materials. These interactions suggest a dynamic connection between collective excitations of spins, quantized as magnons, and elastic waves generated by perturbations in the crystal lattice, quantized as phonons. Both magnons and their associated magnon-phonon excitations can act as sources of spin pumping from magnetic materials into non-magnetic metals. Although …