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Retrieval-Augmented Generation (RAG) merges retrieval methods with deep learning advancements to address the static limitations of large language models (LLMs) by enabling the dynamic integration of up-to-date external information. This…

Information Retrieval · Computer Science 2026-05-19 Yizheng Huang , Jimmy Huang

We propose a procedure which allows one to construct local symmetry generators of general quadratic Lagrangian theory. Manifest recurrence relations for generators in terms of so-called structure matrices of the Dirac formalism are…

High Energy Physics - Theory · Physics 2008-11-26 A. A. Deriglazov

The divergent part of the generating functional of the Resonance Chiral Theory is evaluated up to one loop when one multiplet of scalar an pseudoscalar resonances are included and interaction terms which couple up to two resonances are…

High Energy Physics - Phenomenology · Physics 2011-07-19 I. Rosell

An alternative class of the Lagrangian called the multiplicative form is suc- cessfully derived for a system with one degree of freedom for both non-relativistic and relativistic cases. This new Lagrangian can be considered as a…

Mathematical Physics · Physics 2017-02-01 Kittikun Surawuttinack , Sikarin Yoo-Kong , Monsit Tanasittikosol

We discuss the limitations of the covariant derivative expansion prescription advocated to compute the one-loop Standard Model (SM) effective lagrangian when the heavy fields couple linearly to the SM. In particular, one-loop contributions…

High Energy Physics - Phenomenology · Physics 2016-05-25 Francisco del Aguila , Zoltan Kunszt , Jose Santiago

Retrieval-Augmented Generation (RAG) enables large language models (LLMs) to access external knowledge sources, but the effectiveness of RAG relies on the coordination between the retriever and the generator. Since these components are…

Computation and Language · Computer Science 2025-09-24 Junlin Wang , Zehao Wu , Shaowei Lu , Yanlan Li , Xinghao Huang

Despite their remarkable capabilities, large language models (LLMs) often produce responses containing factual inaccuracies due to their sole reliance on the parametric knowledge they encapsulate. Retrieval-Augmented Generation (RAG), an ad…

Computation and Language · Computer Science 2023-10-19 Akari Asai , Zeqiu Wu , Yizhong Wang , Avirup Sil , Hannaneh Hajishirzi

A common and effective means for improving language model capabilities involves finetuning a ``student'' language model's parameters on generations from a more proficient ``teacher'' model. Termed ``synthetic data'', these generations are…

Diagrammatic rules are developed for simplifying two-loop QED diagrams with propagators in a constant self-dual background field. This diagrammatic analysis, using dimensional regularization, is used to explain how the fully renormalized…

High Energy Physics - Theory · Physics 2010-02-03 Gerald V. Dunne

Graph Retrieval-Augmented Generation (Graph RAG) effectively builds a knowledge graph (KG) to connect disparate facts across a large document corpus. However, this broad-view approach often lacks the deep structured reasoning needed for…

Computation and Language · Computer Science 2025-10-27 Jiaoyang Li , Junhao Ruan , Shengwei Tang , Saihan Chen , Kaiyan Chang , Yuan Ge , Tong Xiao , Jingbo Zhu

It is argued that constituent quarks live in an effective theory that possesses an approximate conformal invariance. An effective lagrangian is constructed which in the large-$\nc$ approximation incorporates Regge asymptotic constraints.…

High Energy Physics - Phenomenology · Physics 2009-10-28 S. R. Beane , U. van Kolck

The systematization of the purely Lagrangean approach to constrained systems in the form of an algorithm involves the iterative construction of a generalized Hessian matrix W taking a rectangular form. This Hessian will exhibit as many left…

High Energy Physics - Theory · Physics 2008-11-26 Heinz J. Rothe , Klaus D. Rothe

Quantizing any model in which a Lagrange multiplier (LM) field is used to restrict field configurations to those that satisfy the classical equations of motion, leads to at most one-loop radiative corrections. This approach can be used with…

High Energy Physics - Theory · Physics 2023-04-24 F. T. Brandt , J. Frenkel , S. Martins-Filho , D. G. C. McKeon

We consider a self-interacting scalar field theory in a slowly varying gravitational background field. Using zeta-function regularization and heat-kernel techniques, we derive the one-loop effective Lagrangian up to second order in the…

High Energy Physics - Theory · Physics 2009-10-22 Klaus Kirsten , Guido Cognola , Luciano Vanzo

In these proceedings we explore the use of (non-linear) electroweak chiral Lagrangians for the description of possible beyond the Standard Model strong dynamics in the electroweak sector. Experimentally one observes an approximate…

High Energy Physics - Phenomenology · Physics 2015-06-23 J. J. Sanz-Cillero

We investigate the perturbative integrability of different quantum field theories in 1+1 dimensions at one loop. Starting from massive bosonic Lagrangians with polynomial-like potentials and absence of inelastic processes at the tree level,…

High Energy Physics - Theory · Physics 2023-04-26 Davide Polvara

In a conversational system, dynamically generating follow-up questions based on context can help users explore information and provide a better user experience. Humans are usually able to ask questions that involve some general life…

Artificial Intelligence · Computer Science 2025-06-30 Jianyu Liu , Yi Huang , Sheng Bi , Junlan Feng , Guilin Qi

A discussion of the number of degrees of freedom, and their dynamical properties, in higher-derivative gravitational theories is presented. The complete non-linear sigma model for these degrees of freedom is exhibited using the method of…

High Energy Physics - Theory · Physics 2008-02-03 Ahmed Hindawi , Burt A. Ovrut , Daniel Waldram

Extended scalar and fermion sectors offer new opportunities for generating the observed strong hierarchies in the fermion mass and mixing patterns of the Standard Model (SM). In this work, we elaborate on the prospects of a particular…

High Energy Physics - Phenomenology · Physics 2019-06-17 A. E. Cárcamo Hernández , Sergey Kovalenko , Roman Pasechnik , Ivan Schmidt

This paper introduces an approach for training o1-like RAG models that retrieve and reason over relevant information step by step before generating the final answer. Conventional RAG methods usually perform a single retrieval step before…

Information Retrieval · Computer Science 2025-10-13 Liang Wang , Haonan Chen , Nan Yang , Xiaolong Huang , Zhicheng Dou , Furu Wei