Natural Language Processing
LLaMo: Large Language Model-based Molecular Graph Assistant
·3401 words·16 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Korea University
LLaMo: a novel large molecular graph-language model seamlessly integrates molecular graph encoders and LLMs, achieving state-of-the-art performance in molecule description generation, property predict…
GlotCC: An Open Broad-Coverage CommonCrawl Corpus and Pipeline for Minority Languages
·1865 words·9 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 LMU Munich & Munich Center for Machine Learning
GlotCC: Open multilingual corpus & pipeline for minority languages, exceeding 1000 languages.
Constraint Back-translation Improves Complex Instruction Following of Large Language Models
·3717 words·18 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Tsinghua University
Constraint Back-translation enhances complex instruction following in LLMs by leveraging inherent constraints in existing datasets for efficient high-quality data creation.
BitStack: Fine-Grained Size Control for Compressed Large Language Models in Variable Memory Environments
·6027 words·29 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Fudan University
BitStack: Dynamic LLM sizing for variable memory!
Controlling Language and Diffusion Models by Transporting Activations
·11502 words·54 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Apple
Steering large language and diffusion models is made easy and efficient via Activation Transport (ACT)! This novel framework uses optimal transport theory to precisely control model activations, leadi…
AAAR-1.0: Assessing AI's Potential to Assist Research
·5113 words·25 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Pennsylvania State University
AAAR-1.0 benchmark rigorously evaluates LLMs’ ability to assist in four core research tasks, revealing both potential and limitations.
A Pointer Network-based Approach for Joint Extraction and Detection of Multi-Label Multi-Class Intents
·2316 words·11 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Dialogue Systems
🏢 Computer Science and Engineering Department, IIT Kharagpur
This research introduces MLMCID, a novel pointer network architecture that excels at jointly extracting multiple intent spans and detecting multi-label, multi-class intents from complex, multilingual …
NeuZip: Memory-Efficient Training and Inference with Dynamic Compression of Neural Networks
·2943 words·14 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 University of Alberta
NeuZip dynamically compresses neural network weights, achieving memory-efficient training and inference without performance loss, significantly reducing the memory footprint of large language models.
M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation
·4787 words·23 mins·
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AI Generated
🤗 Daily Papers
Natural Language Processing
Large Language Models
🏢 Alibaba Group
M2RC-EVAL: A new massively multilingual benchmark for repository-level code completion, featuring fine-grained annotations and a large instruction dataset, enabling better evaluation of code LLMs acro…