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Language Modeling

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/amom-nar/amom

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AMOM: Adaptive Masking over Masking for Conditional Masked Language Model

https://github.com/amore-upf/LSTM_ambiguity

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Putting words in context: LSTM language models and lexical ambiguity

https://github.com/amourwaltz/bayeslms

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Bayesian Neural Network Language Modeling for Speech Recognition

https://github.com/amritabh/shield

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Towards Interpretable Hate Speech Detection using Large Language Model-extracted Rationales

https://github.com/amshaker/mobile-videogpt

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Mobile-VideoGPT: Fast and Accurate Video Understanding Language Model

https://github.com/amujika/Fast-Slow-LSTM

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Fast-Slow Recurrent Neural Networks

https://github.com/amurtadha/alclam

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AlcLaM: Arabic Dialectal Language Model

https://github.com/amy-hyunji/routerretriever

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RouterRetriever: Routing over a Mixture of Expert Embedding Models

https://github.com/ana-rogoz/poprero

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PoPreRo: A New Dataset for Popularity Prediction of Romanian Reddit Posts

https://github.com/anaffinis/llm-vs-lawyers

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LLM vs. Lawyers: Identifying a Subset of Summary Judgments in a Large UK Case Law Dataset

https://github.com/anastasiais-ml/glip

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Centered Masking for Language-Image Pre-Training

https://github.com/andotalao24/multistage-collaborative-knowledge-distillation

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Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation

https://github.com/andreamad8/PPCM

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Plug-and-Play Conversational Models

https://github.com/andreawwenyi/hyperpolyglot

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Hyperpolyglot LLMs: Cross-Lingual Interpretability in Token Embeddings

https://github.com/andrespollano/neural_nets-tda

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Detecting out-of-distribution text using topological features of transformer-based language models

https://github.com/andrewbouras/randomnesspaper

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Integrating Randomness in Large Language Models: A Linear Congruential Generator Approach for Generating Clinically Relevant Content

https://github.com/androidarenaagent/androidarena

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Understanding the Weakness of Large Language Model Agents within a Complex Android Environment

https://github.com/andychiangsh/cdgp

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CDGP: Automatic Cloze Distractor Generation based on Pre-trained Language Model

https://github.com/andyjliu/llms-course-project

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Combating Adversarial Attacks with Multi-Agent Debate

https://github.com/andyjliu/persona-steered-generation-bias

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Evaluating Large Language Model Biases in Persona-Steered Generation

https://github.com/andyshih12/mac

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Training and Inference on Any-Order Autoregressive Models the Right Way

https://github.com/andyzoujm/autocast

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Forecasting Future World Events with Neural Networks

https://github.com/anguyen8/TAB

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TAB: Transformer Attention Bottlenecks enable User Intervention and Debugging in Vision-Language Models

https://github.com/aninrusimha/qat-pretrain

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Mitigating the Impact of Outlier Channels for Language Model Quantization with Activation Regularization

https://github.com/anirudh9119/zforcing_nips17

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Z-Forcing: Training Stochastic Recurrent Networks

https://github.com/anisha2102/molecular_facts

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Molecular Facts: Desiderata for Decontextualization in LLM Fact Verification

https://github.com/anjsimmo/zero-shot-crime-detection

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Garbage in, garbage out: Zero-shot detection of crime using Large Language Models

https://github.com/anniedoris/cad-coder

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CAD-Coder: An Open-Source Vision-Language Model for Computer-Aided Design Code Generation

https://github.com/anon23423589675234/zero-shot-reward-models

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ZYN: Zero-Shot Reward Models with Yes-No Questions for RLAIF

https://github.com/anony4paper/quan_study

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Characterizing and Understanding the Behavior of Quantized Models for Reliable Deployment

https://github.com/anonymous-lgtm/toolcommander

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From Allies to Adversaries: Manipulating LLM Tool-Calling through Adversarial Injection

https://github.com/anonymous1100/Distributional-Discrepancy

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Distributional Discrepancy: A Metric for Unconditional Text Generation

https://github.com/anonymousWSDMSubmission/cost-bo

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Reducing Hyperparameter Tuning Costs in ML, Vision and Language Model Training Pipelines via Memoization-Awareness

https://github.com/anonymouscode-computerscience/ride

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RIDE: Enhancing Large Language Model Alignment through Restyled In-Context Learning Demonstration Exemplars

https://github.com/anoopkdcs/redaffectivelm

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REDAffectiveLM: Leveraging Affect Enriched Embedding and Transformer-based Neural Language Model for Readers' Emotion Detection

https://github.com/anosorae/irra

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Cross-Modal Implicit Relation Reasoning and Aligning for Text-to-Image Person Retrieval

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.