337 results
Relevance Newest Most Cited
HLXiON δ Ω Intent Σ Logic Ψ Synth Π Reason Γ Memory Processing: stat.CO
iON AI Synthesis
The search results for "stat.CO" highlight several topics in quantum physics and data analysis. Key findings include seminal experimental results on nondemolition measurements of photon numbers, though the interpretation of these results is debated. Additionally, a study suggests that Bell correlations might be selection artefacts related to initial experimental conditions, while another explores improved methods for calculating transition probabilities in quantum systems. Other topics covered include advancements in dialectal Arabic language models and tools for inferring interpersonal relations from news articles.
Ask iON more → 📚 Find Papers
arxiv.org
On Nondemolition Measurements of Photon Number: A Comment on quant-ph/0612031

Experimental results stated in quant-ph/0612031 are seminal: The authors have realized nondemolition measurements of the photon number. As to the interpretation of the results, it seems to be less than convincing: The treatment of the system state and of the role of measurement is not compatible wit…

quant-ph
arxiv.org
Bell Correlations as Selection Artefacts

We show that Bell correlations may arise as a special sort of selection artefact, produced by ordinary control of the initial state of the experiments concerned. This accounts for nonlocality, without recourse to any direct spacelike causality or influence. The argument improves an earlier proposal …

quant-ph physics.hist-ph
arxiv.org
A case concerning the improved transition probability

As is well known, the existed perturbation theory can be applied to calculations of energy, state and transition probability in many quantum systems. However, there are different paths and methods to improve its calculation precision and efficiency in our view. According to an improved scheme of per…

quant-ph physics.atom-ph
arxiv.org
Saudi-Dialect-ALLaM: LoRA Fine-Tuning for Dialectal Arabic Generation

Large language models (LLMs) for Arabic are still dominated by Modern Standard Arabic (MSA), with limited support for Saudi dialects such as Najdi and Hijazi. This underrepresentation hinders their ability to capture authentic dialectal variation. Using a privately curated Saudi Dialect Instruction …

cs.CL cs.LG
arxiv.org
Building and displaying name relations using automatic unsupervised analysis of newspaper articles

We present a tool that, from automatically recognised names, tries to infer inter-person relations in order to present associated people on maps. Based on an in-house Named Entity Recognition tool, applied on clusters of an average of 15,000 news articles per day, in 15 different languages, we build…

cs.CL cs.IR
arxiv.org
Tell Me: An LLM-powered Mental Well-being Assistant with RAG, Synthetic Dialogue Generation, and Agentic Planning

We present Tell Me, a mental well-being system that leverages advances in large language models to provide accessible, context-aware support for users and researchers. The system integrates three components: (i) a retrieval-augmented generation (RAG) assistant for personalized, knowledge-grounded di…

cs.CL cs.AI cs.HC cs.LG
arxiv.org
Cross-lingual keyword assignment

This paper presents a language-independent approach to controlled vocabulary keyword assignment using the EUROVOC thesaurus. Due to the multilingual nature of EUROVOC, the keywords for a document written in one language can be displayed in all eleven official European Union languages. The mapping of…

cs.CL cs.IR
arxiv.org
Noise-Driven Persona Formation in Reflexive Neural Language Generation

This paper introduces the Luca-Noise Reflex Protocol (LN-RP), a computational framework for analyzing noise-driven persona emergence in large language models. By injecting stochastic noise seeds into the initial generation state, we observe nonlinear transitions in linguistic behavior across 152 gen…

cs.CL
arxiv.org
Liars' Bench: Evaluating Lie Detectors for Language Models

Prior work has introduced techniques for detecting when large language models (LLMs) lie, that is, generate statements they believe are false. However, these techniques are typically validated in narrow settings that do not capture the diverse lies LLMs can generate. We introduce LIARS' BENCH, a tes…

cs.CL cs.AI
semanticscholar.org
NLLG Quarterly arXiv Report 09/24: What are the most influential current AI Papers?

The NLLG (Natural Language Learning&Generation) arXiv reports assist in navigating the rapidly evolving landscape of NLP and AI research across cs.CL, cs.CV, cs.AI, and cs.LG categories. This fourth installment captures a transformative period in AI history - from January 1, 2023, following ChatGPT'…