https://github.com/skydustz/aec-domain-corpora
공식 코드Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC Domain
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Pretrained Domain-Specific Language Model for General Information Retrieval Tasks in the AEC Domain
SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization
Cross-Lingual Speaker Identification Using Distant Supervision
Decoding fMRI Data into Captions using Prefix Language Modeling
Babysit A Language Model From Scratch: Interactive Language Learning by Trials and Demonstrations
LLM-Grounder: Open-Vocabulary 3D Visual Grounding with Large Language Model as an Agent
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences
World-to-Words: Grounded Open Vocabulary Acquisition through Fast Mapping in Vision-Language Models
Slamming: Training a Speech Language Model on One GPU in a Day
Analysing Discrete Self Supervised Speech Representation for Spoken Language Modeling
Enhancing Conversational Search: Large Language Model-Aided Informative Query Rewriting
Scaling Down Semantic Leakage: Investigating Associative Bias in Smaller Language Models
BOLT: Boost Large Vision-Language Model Without Training for Long-form Video Understanding
Evaluating Language Model Context Windows: A "Working Memory" Test and Inference-time Correction
SuffixDecoding: Extreme Speculative Decoding for Emerging AI Applications
A Smart Multimodal Healthcare Copilot with Powerful LLM Reasoning
Query-Efficient Black-Box Red Teaming via Bayesian Optimization
Compressed Context Memory For Online Language Model Interaction
GuidedQuant: Large Language Model Quantization via Exploiting End Loss Guidance
Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models
Pro-Cap: Leveraging a Frozen Vision-Language Model for Hateful Meme Detection
PromptMTopic: Unsupervised Multimodal Topic Modeling of Memes using Large Language Models
Correcting misinformation on social media with a large language model
Test-Time Training on Nearest Neighbors for Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.