activity
20162025
most citedLightRNN: Memory and Computation-Efficient Recurrent Neural Networks

42 citations · 122 across the 21 of their papers we have counts for

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11 papers · 1 filter

cs.CL20241 cited

Raw Text is All you Need: Knowledge-intensive Multi-turn Instruction Tuning for Large Language Model

Xia Hou, Qifeng Li, Jian Yang +8

Instruction tuning as an effective technique aligns the outputs of large language models (LLMs) with human preference. But how to generate the seasonal multi-turn dialogues from ra…

cs.CL2024

UniCoder: Scaling Code Large Language Model via Universal Code

Tao Sun, Linzheng Chai, Jian Yang +6

Intermediate reasoning or acting steps have successfully improved large language models (LLMs) for handling various downstream natural language processing (NLP) tasks. When applyin…

cs.CL20247 cited

xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning

Linzheng Chai, Jian Yang, Tao Sun +8

Chain-of-thought (CoT) has emerged as a powerful technique to elicit reasoning in large language models and improve a variety of downstream tasks. CoT mainly demonstrates excellent…

cs.CL20232 cited

MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction

Tongliang Li, Zixiang Wang, Linzheng Chai +8

Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages. Previous work uses a shared cross-lingual pre-trained mode…

cs.CL20239 cited

HanoiT: Enhancing Context-aware Translation via Selective Context

Jian Yang, Yuwei Yin, Shuming Ma +7

Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or…

cs.CL20231 cited

Multilingual Entity and Relation Extraction from Unified to Language-specific Training

Zixiang Wang, Jian Yang, Tongliang Li +5

Entity and relation extraction is a key task in information extraction, where the output can be used for downstream NLP tasks. Existing approaches for entity and relation extractio…