Copertina

Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zeng, Shenglai, He, Pengfei, Guo, Kai, Zheng, Tianqi, Lu, Hanqing, Xing, Yue, Liu, Hui
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

RbFT: Robust Fine-tuning for Retrieval-Augmented Generation against Retrieval Defects
di: Tu, Yiteng, et al.
Pubblicazione: (2025)

Pre-training vs. Fine-tuning: A Reproducibility Study on Dense Retrieval Knowledge Acquisition
di: Yao, Zheng, et al.
Pubblicazione: (2025)

TCMIIES: A Browser-Based LLM-Powered Intelligent Information Extraction System for Academic Literature
di: Zhao, Hanqing
Pubblicazione: (2026)

Fix Before Search: Benchmarking Agentic Query Visual Pre-processing in Multimodal Retrieval-augmented Generation
di: Zhang, Jiankun, et al.
Pubblicazione: (2026)

FineTuneBench: How well do commercial fine-tuning APIs infuse knowledge into LLMs?
di: Wu, Eric, et al.
Pubblicazione: (2024)

LLM, Reporting In! Medical Information Extraction Across Prompting, Fine-tuning and Post-correction
di: Belmadani, Ikram, et al.
Pubblicazione: (2025)

Haystack Engineering: Context Engineering for Heterogeneous and Agentic Long-Context Evaluation
di: Li, Mufei, et al.
Pubblicazione: (2025)

AFMRL: Attribute-Enhanced Fine-Grained Multi-Modal Representation Learning in E-commerce
di: Zhang, Biao, et al.
Pubblicazione: (2026)

Fine-tuning Small Language Models as Efficient Enterprise Search Relevance Labelers
di: Kang, Yue, et al.
Pubblicazione: (2026)

UNH at CheckThat! 2025: Fine-tuning Vs Prompting in Claim Extraction
di: Wilder, Joe, et al.
Pubblicazione: (2025)

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
di: Wei, Tianxin, et al.
Pubblicazione: (2024)

BM25S: Orders of magnitude faster lexical search via eager sparse scoring
di: Lù, Xing Han
Pubblicazione: (2024)

Text Clustering as Classification with LLMs
di: Huang, Chen, et al.
Pubblicazione: (2024)

Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering
di: Siriwardhana, Shamane, et al.
Pubblicazione: (2021)

Leveraging the Power of LLMs: A Fine-Tuning Approach for High-Quality Aspect-Based Summarization
di: Mullick, Ankan, et al.
Pubblicazione: (2024)

A MapReduce Approach to Effectively Utilize Long Context Information in Retrieval Augmented Language Models
di: Zhang, Gongbo, et al.
Pubblicazione: (2024)

From Text to Context: An Entailment Approach for News Stakeholder Classification
di: Kuila, Alapan, et al.
Pubblicazione: (2024)

DistRAG: Towards Distance-Based Spatial Reasoning in LLMs
di: Schneider, Nicole R, et al.
Pubblicazione: (2025)

Towards a Unified Paradigm: Integrating Recommendation Systems as a New Language in Large Models
di: Zheng, Kai, et al.
Pubblicazione: (2024)

ReFineG: Synergizing Small Supervised Models and LLMs for Low-Resource Grounded Multimodal NER
di: Tang, Jielong, et al.
Pubblicazione: (2025)

mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval
di: Zhang, Xin, et al.
Pubblicazione: (2024)

Towards Comprehensible Recommendation with Large Language Model Fine-tuning
di: Luo, Yunze, et al.
Pubblicazione: (2025)

Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation
di: Liu, Qijiong, et al.
Pubblicazione: (2025)

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement
di: Mousavian, Maryam, et al.
Pubblicazione: (2025)

Sequential-NIAH: A Needle-In-A-Haystack Benchmark for Extracting Sequential Needles from Long Contexts
di: Yu, Yifei, et al.
Pubblicazione: (2025)

From Model-centered to Human-Centered: Revision Distance as a Metric for Text Evaluation in LLMs-based Applications
di: Ma, Yongqiang, et al.
Pubblicazione: (2024)

Knowledge Compression via Question Generation: Enhancing Multihop Document Retrieval without Fine-tuning
di: Eponon, Anvi Alex, et al.
Pubblicazione: (2025)

Evaluating LLM-based Approaches to Legal Citation Prediction: Domain-specific Pre-training, Fine-tuning, or RAG? A Benchmark and an Australian Law Case Study
di: Han, Jiuzhou, et al.
Pubblicazione: (2024)

Taxonomy-Guided Zero-Shot Recommendations with LLMs
di: Liang, Yueqing, et al.
Pubblicazione: (2024)

From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation
di: Zheng, Pujun, et al.
Pubblicazione: (2026)

Towards Fine-Grained Citation Evaluation in Generated Text: A Comparative Analysis of Faithfulness Metrics
di: Zhang, Weijia, et al.
Pubblicazione: (2024)

Trust or Abstain? A Self-Aware RAG Approach
di: Zhu, Xi, et al.
Pubblicazione: (2026)

TQA-Bench: Evaluating LLMs for Multi-Table Question Answering with Scalable Context and Symbolic Extension
di: Qiu, Zipeng, et al.
Pubblicazione: (2024)

ZeQR: Zero-shot Query Reformulation for Conversational Search
di: Yang, Dayu, et al.
Pubblicazione: (2023)

Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQL
di: Nahid, Md Mahadi Hasan, et al.
Pubblicazione: (2025)

Quantifying and Mitigating Selection Bias in LLMs: A Transferable LoRA Fine-Tuning and Efficient Majority Voting Approach
di: Guda, Blessed, et al.
Pubblicazione: (2025)

Toward Effective Multi-Domain Rumor Detection in Social Networks Using Domain-Gated Mixture-of-Experts
di: Sheikhqoraei, Mohadeseh, et al.
Pubblicazione: (2026)

Topic mining based on fine-tuning Sentence-BERT and LDA
di: Li, Jianheng, et al.
Pubblicazione: (2025)

Unstructured Evidence Attribution for Long Context Query Focused Summarization
di: Wright, Dustin, et al.
Pubblicazione: (2025)

A Representation Sharpening Framework for Zero Shot Dense Retrieval
di: Ashok, Dhananjay, et al.
Pubblicazione: (2025)