Peitian Zhang

Orcid: 0009-0007-1926-7433

According to our database1, Peitian Zhang authored at least 33 papers between 2021 and 2025.

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

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2025
Task-Aware KV Compression For Cost-Effective Long Video Understanding.
CoRR, June, 2025

From Matching to Generation: A Survey on Generative Information Retrieval.
ACM Trans. Inf. Syst., May, 2025

Does RAG Really Perform Bad For Long-Context Processing?
CoRR, February, 2025

Search-o1: Agentic Search-Enhanced Large Reasoning Models.
CoRR, January, 2025

MemoRAG: Boosting Long Context Processing with Global Memory-Enhanced Retrieval Augmentation.
Proceedings of the ACM on Web Conference 2025, 2025

Tackling the Length Barrier: Dynamic Context Browsing for Knowledge-Intensive Task.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Long Context Compression with Activation Beacon.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Boosting Long-Context Information Seeking via Query-Guided Activation Refilling.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
Boosting Long-Context Management via Query-Guided Activation Refilling.
CoRR, 2024

Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding.
CoRR, 2024

MemoRAG: Moving towards Next-Gen RAG Via Memory-Inspired Knowledge Discovery.
CoRR, 2024

Are Long-LLMs A Necessity For Long-Context Tasks?
CoRR, 2024

Extending Llama-3's Context Ten-Fold Overnight.
CoRR, 2024

Extensible Embedding: A Flexible Multipler For LLM's Context Length.
CoRR, 2024

BGE M3-Embedding: Multi-Lingual, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.
CoRR, 2024

Flexibly Scaling Large Language Models Contexts Through Extensible Tokenization.
CoRR, 2024

Soaring from 4K to 400K: Extending LLM's Context with Activation Beacon.
CoRR, 2024

Generative Retrieval via Term Set Generation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

C-Pack: Packed Resources For General Chinese Embeddings.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

A Multi-Task Embedder For Retrieval Augmented LLMs.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

LM-Cocktail: Resilient Tuning of Language Models via Model Merging.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

An Element is Worth a Thousand Words: Enhancing Legal Case Retrieval by Incorporating Legal Elements.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

M3-Embedding: Multi-Linguality, Multi-Functionality, Multi-Granularity Text Embeddings Through Self-Knowledge Distillation.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

INTERS: Unlocking the Power of Large Language Models in Search with Instruction Tuning.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Retrieve Anything To Augment Large Language Models.
CoRR, 2023

C-Pack: Packaged Resources To Advance General Chinese Embedding.
CoRR, 2023

Term-Sets Can Be Strong Document Identifiers For Auto-Regressive Search Engines.
CoRR, 2023

Hybrid Inverted Index Is a Robust Accelerator for Dense Retrieval.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022
Bi-Phase Enhanced IVFPQ for Time-Efficient Ad-hoc Retrieval.
CoRR, 2022

Ultron: An Ultimate Retriever on Corpus with a Model-based Indexer.
CoRR, 2022

GateFormer: Speeding Up News Feed Recommendation with Input Gated Transformers.
CoRR, 2022

2021
Learning to Select Historical News Articles for Interaction based Neural News Recommendation.
CoRR, 2021


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