Xuebo Liu

Orcid: 0000-0001-8524-2006

Affiliations:
  • Harbin Institute of Technology, School of Computer Science and Technology, Shenzhen, China
  • University of Macau, Taipa, Macau (former)


According to our database1, Xuebo Liu authored at least 92 papers between 2019 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Loong: A Human-Like Long Document Translation Agent with Observe-and-Act Adaptive Context Selection.
CoRR, May, 2026

Mitigating Context-Memory Conflicts in LLMs through Dynamic Cognitive Reconciliation Decoding.
CoRR, May, 2026

CoCoReviewBench: A Completeness- and Correctness-Oriented Benchmark for AI Reviewers.
CoRR, May, 2026

MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems.
CoRR, May, 2026

OGER: A Robust Offline-Guided Exploration Reward for Hybrid Reinforcement Learning.
CoRR, April, 2026

D-QRELO: Training- and Data-Free Delta Compression for Large Language Models via Quantization and Residual Low-Rank Approximation.
CoRR, April, 2026

Domain Adaptive Machine Translation with Synthetic Feedback for Large Language Models.
ACM Trans. Asian Low Resour. Lang. Inf. Process., March, 2026

NoveltyAgent: Autonomous Novelty Reporting Agent with Point-wise Novelty Analysis and Self-Validation.
CoRR, March, 2026

RouterKGQA: Specialized-General Model Routing for Constraint-Aware Knowledge Graph Question Answering.
CoRR, March, 2026

Orchestrating Prompt Expertise: Enhancing Knowledge Distillation via Expert-Guided Tuning.
ACM Trans. Asian Low Resour. Lang. Inf. Process., February, 2026

AgentDropoutV2: Optimizing Information Flow in Multi-Agent Systems via Test-Time Rectify-or-Reject Pruning.
CoRR, February, 2026

Stop Rewarding Hallucinated Steps: Faithfulness-Aware Step-Level Reinforcement Learning for Small Reasoning Models.
CoRR, February, 2026

PACE: Defying the Scaling Hypothesis of Exploration in Iterative Alignment for Mathematical Reasoning.
CoRR, February, 2026

Think Dense, Not Long: Dynamic Decoupled Conditional Advantage for Efficient Reasoning.
CoRR, February, 2026

CVeDRL: An Efficient Code Verifier via Difficulty-aware Reinforcement Learning.
CoRR, January, 2026

Exploiting Multimodal Knowledge Graph for Multimodal Machine Translation.
IEEE Trans. Multim., 2026

Exploring and enhancing the transfer of distribution in knowledge distillation for autoregressive language models.
Knowl. Based Syst., 2026

DeReA: Improving Idiom Translation with Detect-Retrieve-Arbitrate Reasoning.
Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Exposing the Cracks: Vulnerabilities of Retrieval-Augmented LLM-based Machine Translation.
Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025
Jailbreak-R1: Exploring the Jailbreak Capabilities of LLMs via Reinforcement Learning.
CoRR, June, 2025

REA-RL: Reflection-Aware Online Reinforcement Learning for Efficient Large Reasoning Models.
CoRR, May, 2025

Dynamic Sampling that Adapts: Iterative DPO for Self-Aware Mathematical Reasoning.
CoRR, May, 2025

Benchmarking Post-Training Quantization in LLMs: Comprehensive Taxonomy, Unified Evaluation, and Comparative Analysis.
CoRR, February, 2025

DelTA: An Online Document-Level Translation Agent Based on Multi-Level Memory.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DynamicKV: Task-Aware Adaptive KV Cache Compression for Long Context LLMs.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Weight-Aware Activation Sparsity with Constrained Bayesian Optimization Scheduling for Large Language Models.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

AgentInit: Initializing LLM-based Multi-Agent Systems via Diversity and Expertise Orchestration for Effective and Efficient Collaboration.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

SeaPO: Strategic Error Amplification for Robust Preference Optimization of Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

CDT: A Comprehensive Capability Framework for Large Language Models Across Cognition, Domain, and Task.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

Runaway is Ashamed, But Helpful: On the Early-Exit Behavior of Large Language Model-based Agents in Embodied Environments.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2025, 2025

AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Who Wrote This? The Key to Zero-Shot LLM-Generated Text Detection Is GECScore.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

UnrealLLM: Towards Highly Controllable and Interactable 3D Scene Generation by LLM-powered Procedural Content Generation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

DRPruning: Efficient Large Language Model Pruning through Distributionally Robust Optimization.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

SGIC: A Self-Guided Iterative Calibration Framework for RAG.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Knowledge Editing with Dynamic Knowledge Graphs for Multi-Hop Question Answering.
Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024
Parameter-Efficient and Student-Friendly Knowledge Distillation.
IEEE Trans. Multim., 2024

DRPruning: Efficient Large Language Model Pruning through Distributionally Robust Optimization.
CoRR, 2024

Exploring and Enhancing the Transfer of Distribution in Knowledge Distillation for Autoregressive Language Models.
CoRR, 2024

SelectIT: Selective Instruction Tuning for Large Language Models via Uncertainty-Aware Self-Reflection.
CoRR, 2024

Understanding and Improving Low-Resource Neural Machine Translation with Shallow Features.
Proceedings of the Natural Language Processing and Chinese Computing, 2024

SelectIT: Selective Instruction Tuning for LLMs via Uncertainty-Aware Self-Reflection.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates.
Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Self-Powered LLM Modality Expansion for Large Speech-Text Models.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

CommonIT: Commonality-Aware Instruction Tuning for Large Language Models via Data Partitions.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Curriculum Consistency Learning for Conditional Sentence Generation.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

LPZero: Language Model Zero-cost Proxy Search from Zero.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Can LLMs Learn Uncertainty on Their Own? Expressing Uncertainty Effectively in A Self-Training Manner.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

EvalCrafter: Benchmarking and Evaluating Large Video Generation Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Pluggable Neural Machine Translation Models via Memory-augmented Adapters.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

LRQuant: Learnable and Robust Post-Training Quantization for Large Language Models.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Speech Sense Disambiguation: Tackling Homophone Ambiguity in End-to-End Speech Translation.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

TasTe: Teaching Large Language Models to Translate through Self-Reflection.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Domain-Aware k-Nearest-Neighbor Knowledge Distillation for Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Revisiting Demonstration Selection Strategies in In-Context Learning.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Towards Demonstration-Aware Large Language Models for Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Improving Attributed Text Generation of Large Language Models via Preference Learning.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

DB-LLM: Accurate Dual-Binarization for Efficient LLMs.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Holistic Exploration on Universal Decompositional Semantic Parsing: Architecture, Data Augmentation, and LLM Paradigm.
CoRR, 2023

TempoSum: Evaluating the Temporal Generalization of Abstractive Summarization.
CoRR, 2023

PromptST: Abstract Prompt Learning for End-to-End Speech Translation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Making the Most of ChatGPT for Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Clustering Pseudo Language Family in Multilingual Translation Models with Fisher Information Matrix.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Can LMs Generalize to Future Data? An Empirical Analysis on Text Summarization.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Revisiting Token Dropping Strategy in Efficient BERT Pretraining.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Test-time Adaptation for Machine Translation Evaluation by Uncertainty Minimization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

kNN-TL: k-Nearest-Neighbor Transfer Learning for Low-Resource Neural Machine Translation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

TemplateGEC: Improving Grammatical Error Correction with Detection Template.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

TransGEC: Improving Grammatical Error Correction with Translationese.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Revisiting Commonsense Reasoning in Machine Translation: Training, Evaluation and Challenge.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Improving Simultaneous Machine Translation with Monolingual Data.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation.
CoRR, 2022

Breaking the Representation Bottleneck of Chinese Characters: Neural Machine Translation with Stroke Sequence Modeling.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ConsistTL: Modeling Consistency in Transfer Learning for Low-Resource Neural Machine Translation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Revisiting Grammatical Error Correction Evaluation and Beyond.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ODE Transformer: An Ordinary Differential Equation-Inspired Model for Sequence Generation.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021
Exploiting Translation Model for Parallel Corpus Mining.
IEEE ACM Trans. Audio Speech Lang. Process., 2021

Variance-Aware Machine Translation Test Sets.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Understanding and Improving Lexical Choice in Non-Autoregressive Translation.
Proceedings of the 9th International Conference on Learning Representations, 2021

Understanding and Improving Encoder Layer Fusion in Sequence-to-Sequence Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Difficulty-Aware Machine Translation Evaluation.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

On the Copying Behaviors of Pre-Training for Neural Machine Translation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Progressive Multi-Granularity Training for Non-Autoregressive Translation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Rejuvenating Low-Frequency Words: Making the Most of Parallel Data in Non-Autoregressive Translation.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Meta-Curriculum Learning for Domain Adaptation in Neural Machine Translation.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Norm-Based Curriculum Learning for Neural Machine Translation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Latent Attribute Based Hierarchical Decoder for Neural Machine Translation.
IEEE ACM Trans. Audio Speech Lang. Process., 2019

Shared-Private Bilingual Word Embeddings for Neural Machine Translation.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019


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