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08/24/2023
Large Language Model as Autonomous Decision Maker
While large language models (LLMs) exhibit impressive language understan...
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08/21/2023
AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors in Agents
Autonomous agents empowered by Large Language Models (LLMs) have undergo...
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07/31/2023
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Despite the advancements of open-source large language models (LLMs) and...
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07/28/2023
Exploring Format Consistency for Instruction Tuning
Instruction tuning has emerged as a promising approach to enhancing larg...
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06/04/2023
Arbitrary Few Parameters are Good Enough for Adapting Large-scale Pre-trained Language Models
Parameter-efficient tuning (PET) methods can effectively drive extremely...
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05/23/2023
CREATOR: Disentangling Abstract and Concrete Reasonings of Large Language Models through Tool Creation
Large Language Models (LLMs) have demonstrated significant progress in u...
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05/23/2023
Enhancing Chat Language Models by Scaling High-quality Instructional Conversations
Fine-tuning on instruction data has been widely validated as an effectiv...
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05/15/2023
Recyclable Tuning for Continual Pre-training
Continual pre-training is the paradigm where pre-trained language models...
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05/11/2023
WebCPM: Interactive Web Search for Chinese Long-form Question Answering
Long-form question answering (LFQA) aims at answering complex, open-ende...
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04/17/2023
Tool Learning with Foundation Models
Humans possess an extraordinary ability to create and utilize tools, all...
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02/19/2023
Human Emotion Knowledge Representation Emerges in Large Language Model and Supports Discrete Emotion Inference
How humans infer discrete emotions is a fundamental research question in...
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10/25/2022
Exploring Mode Connectivity for Pre-trained Language Models
Recent years have witnessed the prevalent application of pre-trained lan...
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10/24/2022
Different Tunes Played with Equal Skill: Exploring a Unified Optimization Subspace for Delta Tuning
Delta tuning (DET, also known as parameter-efficient tuning) is deemed a...
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03/12/2022
ELLE: Efficient Lifelong Pre-training for Emerging Data
Current pre-trained language models (PLM) are typically trained with sta...
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11/12/2021
On Transferability of Prompt Tuning for Natural Language Understanding
Prompt tuning (PT) is a promising parameter-efficient method to utilize ...
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10/15/2021
Exploring Low-dimensional Intrinsic Task Subspace via Prompt Tuning
How can pre-trained language models (PLMs) learn universal representatio...
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05/28/2021
Knowledge Inheritance for Pre-trained Language Models
Recent explorations of large-scale pre-trained language models (PLMs) su...
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12/30/2020
ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning
Pre-trained Language Models (PLMs) have shown strong performance in vari...
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12/01/2020
CPM: A Large-scale Generative Chinese Pre-trained Language Model
Pre-trained Language Models (PLMs) have proven to be beneficial for vari...
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11/04/2019
Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations
Deep neural networks usually require massive labeled data, which restric...
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11/04/2019