Copertina

Augmenting Transformers with Recursively Composed Multi-grained Representations

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Hu, Xiang, Zhu, Qingyang, Tu, Kewei, Wu, Wei
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Generative Pretrained Structured Transformers: Unsupervised Syntactic Language Models at Scale
di: Hu, Xiang, et al.
Pubblicazione: (2024)

A Systematic Study of Compositional Syntactic Transformer Language Models
di: Zhao, Yida, et al.
Pubblicazione: (2025)

Efficient Length-Generalizable Attention via Causal Retrieval for Long-Context Language Modeling
di: Hu, Xiang, et al.
Pubblicazione: (2024)

Hardware-aligned Hierarchical Sparse Attention for Efficient Long-term Memory Access
di: Hu, Xiang, et al.
Pubblicazione: (2025)

Dependency Transformer Grammars: Integrating Dependency Structures into Transformer Language Models
di: Zhao, Yida, et al.
Pubblicazione: (2024)

Flash Multi-Head Feed-Forward Network
di: Zhang, Minshen, et al.
Pubblicazione: (2025)

Learning Robust Named Entity Recognizers From Noisy Data With Retrieval Augmentation
di: Ai, Chaoyi, et al.
Pubblicazione: (2024)

Unsupervised Morphological Tree Tokenizer
di: Zhu, Qingyang, et al.
Pubblicazione: (2024)

Multi-Aspect Controllable Text Generation with Disentangled Counterfactual Augmentation
di: Liu, Yi, et al.
Pubblicazione: (2024)

TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation
di: Wang, Peng, et al.
Pubblicazione: (2024)

Repurposing Synthetic Data for Fine-grained Search Agent Supervision
di: Zhao, Yida, et al.
Pubblicazione: (2025)

Augmenting Math Word Problems via Iterative Question Composing
di: Liu, Haoxiong, et al.
Pubblicazione: (2024)

Knowledge Graph-Guided Retrieval Augmented Generation
di: Zhu, Xiangrong, et al.
Pubblicazione: (2025)

RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
di: Ru, Dongyu, et al.
Pubblicazione: (2024)

State Representation and Termination for Recursive Reasoning Systems
di: Guha, Debashis, et al.
Pubblicazione: (2026)

Limits of Transformer Language Models on Learning to Compose Algorithms
di: Thomm, Jonathan, et al.
Pubblicazione: (2024)

OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations
di: Chen, Jiangwang, et al.
Pubblicazione: (2026)

Region-R1: Reinforcing Query-Side Region Cropping for Multi-Modal Re-Ranking
di: Hu, Chan-Wei, et al.
Pubblicazione: (2026)

mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation
di: Hu, Chan-Wei, et al.
Pubblicazione: (2025)

Recursive Multi-Agent Systems
di: Yang, Xiyuan, et al.
Pubblicazione: (2026)

Knowledge Pyramid Construction for Multi-Level Retrieval-Augmented Generation
di: Chen, Rubing, et al.
Pubblicazione: (2024)

Learning Composable Chains-of-Thought
di: Yin, Fangcong, et al.
Pubblicazione: (2025)

HarmTransform: Transforming Explicit Harmful Queries into Stealthy via Multi-Agent Debate
di: Zhu, Shenzhe
Pubblicazione: (2025)

MRAG: Benchmarking Retrieval-Augmented Generation for Bio-medicine
di: Li, Liz, et al.
Pubblicazione: (2026)

ToolPlanner: A Tool Augmented LLM for Multi Granularity Instructions with Path Planning and Feedback
di: Wu, Qinzhuo, et al.
Pubblicazione: (2024)

RELOOP: Recursive Retrieval with Multi-Hop Reasoner and Planners for Heterogeneous QA
di: Yang, Ruiyi, et al.
Pubblicazione: (2025)

Self-Discover: Large Language Models Self-Compose Reasoning Structures
di: Zhou, Pei, et al.
Pubblicazione: (2024)

The Other Side of the Coin: Exploring Fairness in Retrieval-Augmented Generation
di: Zhang, Zheng, et al.
Pubblicazione: (2025)

Recursive Language Models
di: Zhang, Alex L., et al.
Pubblicazione: (2025)

Active Use of Latent Constituency Representation in both Humans and Large Language Models
di: Liu, Wei, et al.
Pubblicazione: (2024)

Avoiding Knowledge Edit Skipping in Multi-hop Question Answering with Guided Decomposition
di: Liu, Yi, et al.
Pubblicazione: (2025)

MatryoshkaThinking: Recursive Test-Time Scaling Enables Efficient Reasoning
di: Chen, Hongwei, et al.
Pubblicazione: (2025)

RNG: Reducing Multi-level Noise and Multi-grained Semantic Gap for Joint Multimodal Aspect-Sentiment Analysis
di: Liu, Yaxin, et al.
Pubblicazione: (2024)

ArcAligner: Adaptive Recursive Aligner for Compressed Context Embeddings in RAG
di: Li, Jianbo, et al.
Pubblicazione: (2026)

Encyclo-K: Evaluating LLMs with Dynamically Composed Knowledge Statements
di: Liang, Yiming, et al.
Pubblicazione: (2025)

How Do Language Models Compose Functions?
di: Khandelwal, Apoorv, et al.
Pubblicazione: (2025)

Abstract Meaning Representation-Based Logic-Driven Data Augmentation for Logical Reasoning
di: Bao, Qiming, et al.
Pubblicazione: (2023)

Learning to Compress: Unlocking the Potential of Large Language Models for Text Representation
di: Zhang, Yeqin, et al.
Pubblicazione: (2025)

CORBA: Contagious Recursive Blocking Attacks on Multi-Agent Systems Based on Large Language Models
di: Zhou, Zhenhong, et al.
Pubblicazione: (2025)

Compose and Fuse: Revisiting the Foundational Bottlenecks in Multimodal Reasoning
di: Wang, Yucheng, et al.
Pubblicazione: (2025)