Tootfinder

Ich werde das Wochenende einfach ausschliesslich mit „kucken“ verbringen. Bin noch nicht so sicher, ob mein Hirn das hinbekommt, was der allerbeste Optiker überhaupt mir eingeschliffen hat. Solange ich mich nicht bewege und die Welt auch nicht, geht’s 🤓
Ah: Früpensionierung wäre eine Option, einfach wo sitzen und langsam kucken

Optimization for Semantic-Aware Resource Allocation under CPT-based Utilities
Symeon Vaidanis, Photios A. Stavrou, Marios Kountouris
https://arxiv.org/abs/2506.04952

Optimization for Semantic-Aware Resource Allocation under CPT-based Utilities
The problem of resource allocation in goal-oriented semantic communication with semantic-aware utilities and subjective risk perception is studied here. By linking information importance to risk aversion, we model agent behavior using Cumulative Prospect Theory (CPT), which incorporates risk-sensitive utility functions and nonlinear transformations of distributions, reflecting subjective perceptions of gains and losses. The objective is to maximize the aggregate utility across multiple CPT-mode…

If you could rename the Social Icons block to reflect that it also supports contact options like Phone and Email, what name would you give it? #WordPress

CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward
Shudong Liu, Hongwei Liu, Junnan Liu, Linchen Xiao, Songyang Gao, Chengqi Lyu, Yuzhe Gu, Wenwei Zhang, Derek F. Wong, Songyang Zhang, Kai Chen
https://arxiv.org/abs/2508.03686

CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome Reward
Answer verification is crucial not only for evaluating large language models (LLMs) by matching their unstructured outputs against standard answers, but also serves as the reward model to guide LLM optimization. Most evaluation frameworks rely on regularized matching or employ general LLMs for answer verification, which demands extensive, repetitive customization for regex rules or evaluation prompts. Two fundamental limitations persist in current methodologies: 1) the absence of comprehensive …

Exp4Fuse: A Rank Fusion Framework for Enhanced Sparse Retrieval using Large Language Model-based Query Expansion
Lingyuan Liu, Mengxiang Zhang
https://arxiv.org/abs/2506.04760

Exp4Fuse: A Rank Fusion Framework for Enhanced Sparse Retrieval using Large Language Model-based Query Expansion
Large Language Models (LLMs) have shown potential in generating hypothetical documents for query expansion, thereby enhancing information retrieval performance. However, the efficacy of this method is highly dependent on the quality of the generated documents, which often requires complex prompt strategies and the integration of advanced dense retrieval techniques. This can be both costly and computationally intensive. To mitigate these limitations, we explore the use of zero-shot LLM-based que…

LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Fangfu Liu, Hao Li, Jiawei Chi, Hanyang Wang, Minghui Yang, Fudong Wang, Yueqi Duan
https://arxiv.org/abs/2507.02813

LangScene-X: Reconstruct Generalizable 3D Language-Embedded Scenes with TriMap Video Diffusion
Recovering 3D structures with open-vocabulary scene understanding from 2D images is a fundamental but daunting task. Recent developments have achieved this by performing per-scene optimization with embedded language information. However, they heavily rely on the calibrated dense-view reconstruction paradigm, thereby suffering from severe rendering artifacts and implausible semantic synthesis when limited views are available. In this paper, we introduce a novel generative framework, coined LangS…

LEO: An Open-Source Platform for Linking OMERO with Lab Notebooks and Heterogeneous Metadata Sources
Rodrigo Escobar D\'iaz Guerrero, Jamile Mohammad Jafari, Tobias Meyer-Zedler, Michael Schmitt, Juergen Popp, Thomas Bocklitz
https://arxiv.org/abs/2508.00654

LEO: An Open-Source Platform for Linking OMERO with Lab Notebooks and Heterogeneous Metadata Sources
In the interdisciplinary field of microscopy research, managing and integrating large volumes of data stored across disparate platforms remains a major challenge. Data types such as bioimages, experimental records, and spectral information are often maintained in separate repositories, each following different management standards. However, linking these data sources across the research lifecycle is essential to align with the FAIR principles of data management: Findability, Accessibility, Inte…

ReDSM5: A Reddit Dataset for DSM-5 Depression Detection
Eliseo Bao, Anxo P\'erez, Javier Parapar
https://arxiv.org/abs/2508.03399 https://arxiv.org/pdf…

ReDSM5: A Reddit Dataset for DSM-5 Depression Detection
Depression is a pervasive mental health condition that affects hundreds of millions of individuals worldwide, yet many cases remain undiagnosed due to barriers in traditional clinical access and pervasive stigma. Social media platforms, and Reddit in particular, offer rich, user-generated narratives that can reveal early signs of depressive symptomatology. However, existing computational approaches often label entire posts simply as depressed or not depressed, without linking language to specif…

There’s exactly 1 narrow way that it’s true. Before widespread #WFH, attackers often had an insurmountable barrier: no way into the business network from the Internet. At the last gig (2008) where I had to visit a “workplace” regularly, inbound remote access was officially non-existent & outbound Internet access all went through restrictive web proxies.

Kevin Beaumont (@GossiTheDog@cyberplace.social)
Attached: 1 image This Daily Mail piece about security leaders thinking work-from-home means they will be crippled is horseshit, I'm not linking it. They've taken a survey about how security people think their businesses couldn't survive ransomware, and linked it to working from home. WFH isn't the problem: business IT and resilience being built on quicksand is the problem.

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval
Lingyuan Liu, Mengxiang Zhang
https://arxiv.org/abs/2506.04762

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval
Large language models (LLMs)-based query expansion for information retrieval augments queries with generated hypothetical documents with LLMs. However, its performance relies heavily on the scale of the language models (LMs), necessitating larger, more advanced LLMs. This approach is costly, computationally intensive, and often has limited accessibility. To address these limitations, we introduce GOLFer - Smaller LMs-Generated Documents Hallucination Filter & Combiner - a novel method leveragin…