Copertina

Enhancing Length Extrapolation in Sequential Models with Pointer-Augmented Neural Memory

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Le, Hung, Nguyen, Dung, Do, Kien, Venkatesh, Svetha, Tran, Truyen
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Multi-Reference Preference Optimization for Large Language Models
di: Le, Hung, et al.
Pubblicazione: (2024)

Stable Hadamard Memory: Revitalizing Memory-Augmented Agents for Reinforcement Learning
di: Le, Hung, et al.
Pubblicazione: (2024)

Reasoning Under 1 Billion: Memory-Augmented Reinforcement Learning for Large Language Models
di: Le, Hung, et al.
Pubblicazione: (2025)

Beyond Surprise: Improving Exploration Through Surprise Novelty
di: Le, Hung, et al.
Pubblicazione: (2023)

Revisiting the Dataset Bias Problem from a Statistical Perspective
di: Do, Kien, et al.
Pubblicazione: (2024)

Finding the Trigger: Causal Abductive Reasoning on Video Events
di: Le, Thao Minh, et al.
Pubblicazione: (2025)

Large Language Models Prompting With Episodic Memory
di: Do, Dai, et al.
Pubblicazione: (2024)

Uncertainty-Guided Checkpoint Selection for Reinforcement Finetuning of Large Language Models
di: Nguyen, Manh, et al.
Pubblicazione: (2025)

Continual Fine-Tuning of Large Language Models via Program Memory
di: Le, Hung, et al.
Pubblicazione: (2026)

Score-based Integrated Gradient for Root Cause Explanations of Outliers
di: Nguyen, Phuoc, et al.
Pubblicazione: (2026)

Hear Both Sides: Efficient Multi-Agent Debate via Diversity-Aware Message Retention
di: Nguyen, Manh, et al.
Pubblicazione: (2026)

Learning Structural Causal Models from Ordering: Identifiable Flow Models
di: Le, Minh Khoa, et al.
Pubblicazione: (2024)

SPaCe: Unlocking Sample-Efficient Large Language Models Training With Self-Pace Curriculum Learning
di: Do, Dai, et al.
Pubblicazione: (2025)

Generating Realistic Tabular Data with Large Language Models
di: Nguyen, Dang, et al.
Pubblicazione: (2024)

ChargeFlow: Flow-Matching Refinement of Charge-Conditioned Electron Densities
di: Nguyen, Tri Minh, et al.
Pubblicazione: (2026)

Progressive Multi-granular Alignments for Grounded Reasoning in Large Vision-Language Models
di: Le, Quang-Hung, et al.
Pubblicazione: (2024)

S2MoE: Robust Sparse Mixture of Experts via Stochastic Learning
di: Do, Giang, et al.
Pubblicazione: (2025)

Rethinking Sparse Mixture of Experts from a Unified Perspective
di: Do, Giang, et al.
Pubblicazione: (2025)

Do Domain-specific Experts exist in MoE-based LLMs?
di: Do, Giang, et al.
Pubblicazione: (2026)

Eigenvectors of Experts are Training-free Non-collapsing Routers
di: Do, Giang, et al.
Pubblicazione: (2026)

SimSMoE: Solving Representational Collapse via Similarity Measure
di: Do, Giang, et al.
Pubblicazione: (2024)

Variable-Agnostic Causal Exploration for Reinforcement Learning
di: Nguyen, Minh Hoang, et al.
Pubblicazione: (2024)

GRAD: Graph-Retrieved Adaptive Decoding for Hallucination Mitigation
di: Nguyen, Manh, et al.
Pubblicazione: (2025)

MP-PINN: A Multi-Phase Physics-Informed Neural Network for Epidemic Forecasting
di: Nguyen, Thang, et al.
Pubblicazione: (2024)

Large Language Models for Imbalanced Classification: Diversity makes the difference
di: Nguyen, Dang, et al.
Pubblicazione: (2025)

From Interpolation to Extrapolation: Complete Length Generalization for Arithmetic Transformers
di: Duan, Shaoxiong, et al.
Pubblicazione: (2023)

On the Role of Discrete Representation in Sparse Mixture of Experts
di: Do, Giang, et al.
Pubblicazione: (2024)

Automatic Prompt Selection for Large Language Models
di: Do, Viet-Tung, et al.
Pubblicazione: (2024)

Reviving Error Correction in Modern Deep Time-Series Forecasting
di: Nguyen, Minh Hoang, et al.
Pubblicazione: (2026)

Bayesian Optimistic Optimisation with Exponentially Decaying Regret
di: Tran-The, Hung, et al.
Pubblicazione: (2021)

Trading Convergence Rate with Computational Budget in High Dimensional Bayesian Optimization
di: Tran-The, Hung, et al.
Pubblicazione: (2019)

Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks
di: Nguyen, Tri Minh, et al.
Pubblicazione: (2024)

Rethinking Deep Alignment Through The Lens Of Incomplete Learning
di: Bach, Thong, et al.
Pubblicazione: (2025)

Continual Safety Alignment via Gradient-Based Sample Selection
di: Bach, Thong, et al.
Pubblicazione: (2026)

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models
di: Gao, Bo, et al.
Pubblicazione: (2025)

Federated Domain Generalization with Latent Space Inversion
di: Palakkadavath, Ragja, et al.
Pubblicazione: (2025)

Variational Flow Models: Flowing in Your Style
di: Do, Kien, et al.
Pubblicazione: (2024)

Regret Bounds for Expected Improvement Algorithms in Gaussian Process Bandit Optimization
di: Tran-The, Hung, et al.
Pubblicazione: (2022)

Predicting the Reliability of an Image Classifier under Image Distortion
di: Nguyen, Dang, et al.
Pubblicazione: (2024)

Two Stones Hit One Bird: Bilevel Positional Encoding for Better Length Extrapolation
di: He, Zhenyu, et al.
Pubblicazione: (2024)