Copertina

TriSum: Learning Summarization Ability from Large Language Models with Structured Rationale

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Jiang, Pengcheng, Xiao, Cao, Wang, Zifeng, Bhatia, Parminder, Sun, Jimeng, Han, Jiawei
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge
di: Jiang, Pengcheng, et al.
Pubblicazione: (2024)

Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval
di: Jiang, Pengcheng, et al.
Pubblicazione: (2024)

GenRES: Rethinking Evaluation for Generative Relation Extraction in the Era of Large Language Models
di: Jiang, Pengcheng, et al.
Pubblicazione: (2024)

s3: You Don't Need That Much Data to Train a Search Agent via RL
di: Jiang, Pengcheng, et al.
Pubblicazione: (2025)

MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
di: Wen, Yilin, et al.
Pubblicazione: (2023)

PILOT: Legal Case Outcome Prediction with Case Law
di: Cao, Lang, et al.
Pubblicazione: (2024)

Accelerating Clinical Evidence Synthesis with Large Language Models
di: Wang, Zifeng, et al.
Pubblicazione: (2024)

RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generation
di: Jiang, Pengcheng, et al.
Pubblicazione: (2025)

BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models
di: Chang, Aofei, et al.
Pubblicazione: (2024)

Personalized Abstractive Summarization by Tri-agent Generation Pipeline
di: Xiao, Wen, et al.
Pubblicazione: (2023)

Bi-level Contrastive Learning for Knowledge-Enhanced Molecule Representations
di: Jiang, Pengcheng, et al.
Pubblicazione: (2023)

Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector
di: Yang, Haoyan, et al.
Pubblicazione: (2025)

Can Large Language Models Replace Data Scientists in Biomedical Research?
di: Wang, Zifeng, et al.
Pubblicazione: (2024)

A Survey on Retrieval And Structuring Augmented Generation with Large Language Models
di: Jiang, Pengcheng, et al.
Pubblicazione: (2025)

BioDSA-1K: Benchmarking Data Science Agents for Biomedical Research
di: Wang, Zifeng, et al.
Pubblicazione: (2025)

Integration of Large Language Models and Traditional Deep Learning for Social Determinants of Health Prediction
di: Landes, Paul, et al.
Pubblicazione: (2025)

Dynamic Uncertainty Ranking: Enhancing Retrieval-Augmented In-Context Learning for Long-Tail Knowledge in LLMs
di: Yu, Shuyang, et al.
Pubblicazione: (2024)

Rationale-based Opinion Summarization
di: Li, Haoyuan, et al.
Pubblicazione: (2024)

AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Models
di: Cao, Lang, et al.
Pubblicazione: (2024)

Linear Spaces of Meanings: Compositional Structures in Vision-Language Models
di: Trager, Matthew, et al.
Pubblicazione: (2023)

Structure-Augmented Reasoning Generation
di: Parekh, Jash Rajesh, et al.
Pubblicazione: (2025)

TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation
di: Sun, Jiashuo, et al.
Pubblicazione: (2026)

Harness-1: Reinforcement Learning for Search Agents with State-Externalizing Harnesses
di: Jiang, Pengcheng, et al.
Pubblicazione: (2026)

Enhancing Visual-Language Modality Alignment in Large Vision Language Models via Self-Improvement
di: Wang, Xiyao, et al.
Pubblicazione: (2024)

EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations
di: Zhang, Chiyu, et al.
Pubblicazione: (2024)

Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
di: Lin, Zhen, et al.
Pubblicazione: (2023)

Matching Patients to Clinical Trials with Large Language Models
di: Jin, Qiao, et al.
Pubblicazione: (2023)

PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models
di: Zhang, Lemei, et al.
Pubblicazione: (2024)

Panacea: A foundation model for clinical trial search, summarization, design, and recruitment
di: Lin, Jiacheng, et al.
Pubblicazione: (2024)

SumHiS: Extractive Summarization Exploiting Hidden Structure
di: Pavel, Tikhonov, et al.
Pubblicazione: (2024)

A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
di: Zhang, Haopeng, et al.
Pubblicazione: (2024)

DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learning
di: Jiang, Pengcheng, et al.
Pubblicazione: (2025)

ICLEval: Evaluating In-Context Learning Ability of Large Language Models
di: Chen, Wentong, et al.
Pubblicazione: (2024)

On Learning to Summarize with Large Language Models as References
di: Liu, Yixin, et al.
Pubblicazione: (2023)

On Context Utilization in Summarization with Large Language Models
di: Ravaut, Mathieu, et al.
Pubblicazione: (2023)

Structured Reasoning for Large Language Models
di: Han, Jinyi, et al.
Pubblicazione: (2026)

An Empirical Study of Many-to-Many Summarization with Large Language Models
di: Wang, Jiaan, et al.
Pubblicazione: (2025)

QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models
di: Wang, Wei, et al.
Pubblicazione: (2024)

MARE: Multi-Aspect Rationale Extractor on Unsupervised Rationale Extraction
di: Jiang, Han, et al.
Pubblicazione: (2024)

Beyond Label Attention: Transparency in Language Models for Automated Medical Coding via Dictionary Learning
di: Wu, John, et al.
Pubblicazione: (2024)