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Xipeng Qiu

13 papers hereh-index 7245 citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author10

Across the 12 of 13 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.SD2
  • cs.LG1
same name
  • Xipeng Qiu — 129 papers, h 67
  • Xipeng Qiu — 32 papers, h 16
  • Xipeng Qiu — 31 papers, h 18
  • Xipeng Qiu — 28 papers, h 15
  • Xipeng Qiu — 19 papers, h 9
  • Xipeng Qiu — 13 papers, h 12

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedIntrinsicVoice: Empowering LLMs with Intrinsic Real-time Voice Interaction Abilities

2 citations · 2 across the 12 of their papers we have counts for

collaborators
Showing 2024 · cs.CLShow all

4 papers · 2 filters

cs.CL2024

LongSafety: Enhance Safety for Long-Context LLMs

Mianqiu Huang, Xiaoran Liu, Shaojun Zhou +11

Recent advancements in model architectures and length extrapolation techniques have significantly extended the context length of large language models (LLMs), paving the way for th…

cs.CL2024

MetaAlign: Align Large Language Models with Diverse Preferences during Inference Time

Mozhi Zhang, Pengyu Wang, Chenkun Tan +4

Large Language Models (LLMs) acquire extensive knowledge and remarkable abilities from extensive text corpora, making them powerful tools for various applications. To make LLMs mor…

cs.CL2024

SpeechAlign: Aligning Speech Generation to Human Preferences

Dong Zhang, Zhaowei Li, Shimin Li +4

Speech language models have significantly advanced in generating realistic speech, with neural codec language models standing out. However, the integration of human feedback to ali…

cs.CL2024

Calibrating the Confidence of Large Language Models by Eliciting Fidelity

Mozhi Zhang, Mianqiu Huang, Rundong Shi +5

Large language models optimized with techniques like RLHF have achieved good alignment in being helpful and harmless. However, post-alignment, these language models often exhibit o…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.