Language Modelling
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A language model is a model of natural language. Language models are useful for a variety of tasks, including speech recognition, machine translation, natural language generation (generating more human-like text), optical character recognition, route optimization, handwriting recognition, grammar induction, and information retrieval.
Large language models (LLMs), currently their most advanced form, are predominantly based on transformers trained on larger datasets (frequently using words scraped from the public internet). They have superseded recurrent neural network-based models, which had previously superseded the purely statistical models, such as word n-gram language model.
Source: Wikipedia
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/adverifai/Satire_vs_Fake
공식 코드Identifying Nuances in Fake News vs. Satire: Using Semantic and Linguistic Cues
https://github.com/adxcreative/LEARN
공식 코드https://github.com/aehrc/cxrmate
공식 코드Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report Generation
https://github.com/aetherprior/multilingual-sentence-boundary-detection
공식 코드Punctuation Restoration for Singaporean Spoken Languages: English, Malay, and Mandarin
https://github.com/aetting/lm-diagnostics
공식 코드What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models
https://github.com/aeye-lab/emnlp-syntheticscanpaths-nlu-pretrainedlm
공식 코드Pre-Trained Language Models Augmented with Synthetic Scanpaths for Natural Language Understanding
https://github.com/afrozas/skip-thought-gan
공식 코드Generating Text through Adversarial Training using Skip-Thought Vectors
https://github.com/ag1988/dss
공식 코드Diagonal State Spaces are as Effective as Structured State Spaces
https://github.com/ag1988/gmat
공식 코드https://github.com/ag1988/injecting_numeracy
공식 코드https://github.com/ag1988/value_aware_attn
공식 코드https://github.com/ag2ai/ag2
공식 코드Adaptive In-conversation Team Building for Language Model Agents
https://github.com/agarwalishika/delift
공식 코드DELIFT: Data Efficient Language model Instruction Fine Tuning
https://github.com/agemagician/Ankh
공식 코드Ankh: Optimized Protein Language Model Unlocks General-Purpose Modelling
https://github.com/agencyenterprise/promptinject
공식 코드Ignore Previous Prompt: Attack Techniques For Language Models
https://github.com/aghie/parsing-as-pretraining
공식 코드https://github.com/aghyad-deeb/unlearning_evaluation
공식 코드Do Unlearning Methods Remove Information from Language Model Weights?
https://github.com/agi-edgerunners/llm-adapters
공식 코드LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models
https://github.com/agiping/godel-scheduler
공식 코드Topology-aware Preemptive Scheduling for Co-located LLM Workloads
https://github.com/agiresearch/InstructGLM
공식 코드https://github.com/agiresearch/aios
공식 코드https://github.com/agiresearch/autoflow
공식 코드AutoFlow: Automated Workflow Generation for Large Language Model Agents
https://github.com/agiresearch/battleagent
공식 코드BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis
https://github.com/agiresearch/waragent
공식 코드War and Peace (WarAgent): Large Language Model-based Multi-Agent Simulation of World Wars
https://github.com/ahmedssabir/Semantic-Relatedness-Based-Reranker-for-Text-Spotting
공식 코드https://github.com/ahmedssabir/Visual-Semantic-Relatedness-with-Word-Embedding
공식 코드Visual Re-ranking with Natural Language Understanding for Text Spotting
https://github.com/ahoho/inferential-decompositions
공식 코드Natural Language Decompositions of Implicit Content Enable Better Text Representations
https://github.com/ahren09/agentreview
공식 코드https://github.com/ai-agents-2030/SPA-Bench
공식 코드SPA-Bench: A Comprehensive Benchmark for SmartPhone Agent Evaluation
https://github.com/ai-application-and-integration-lab/sam4mllm
공식 코드SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation
https://github.com/ai-da-stc/generative-ai-research-babylm
공식 코드https://github.com/ai-for-public-services/ai-gov-framework
공식 코드Artificial intelligence in government: Concepts, standards, and a unified framework
https://github.com/ai-for-science/mozi
공식 코드MoZIP: A Multilingual Benchmark to Evaluate Large Language Models in Intellectual Property
https://github.com/ai-hpc-research-team/git-mol
공식 코드GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text
https://github.com/ai-hpc-research-team/slm4crp
공식 코드A Self-feedback Knowledge Elicitation Approach for Chemical Reaction Predictions
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.