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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/valentinhofmann/dcwe

공식 코드

Dynamic Contextualized Word Embeddings

https://github.com/valentinhofmann/geoadaptation

공식 코드

Geographic Adaptation of Pretrained Language Models

https://github.com/valentyn1boreiko/llm-threat-model

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A Realistic Threat Model for Large Language Model Jailbreaks

https://github.com/valuebyte-ai/awesome-llm-psychometrics

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Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement

https://github.com/vanderschaarlab/discopop

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Discovering Preference Optimization Algorithms with and for Large Language Models

https://github.com/vanderschaarlab/l2mac

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L2MAC: Large Language Model Automatic Computer for Extensive Code Generation

https://github.com/vansky/neural-complexity

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A Neural Model of Adaptation in Reading

https://github.com/varal7/conformal-language-modeling

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Conformal Language Modeling

https://github.com/varinf/TransformersDataAugmentation

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Data Augmentation using Pre-trained Transformer Models

https://github.com/vasily789/atn

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Breaking Time Invariance: Assorted-Time Normalization for RNNs

https://github.com/vbursztyn/critique-to-preference-emnlp2021

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"It doesn't look good for a date": Transforming Critiques into Preferences for Conversational Recommendation Systems

https://github.com/vcahlik/reasoning-grounded-explanations

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Reasoning-Grounded Natural Language Explanations for Language Models

https://github.com/vcskaushik/LLMzip

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LLMZip: Lossless Text Compression using Large Language Models

https://github.com/vec-ai/wikihow-tiir

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Towards Text-Image Interleaved Retrieval

https://github.com/vectara/mirage-bench

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MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems

https://github.com/vectorspacelab/video-xl

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Video-XL: Extra-Long Vision Language Model for Hour-Scale Video Understanding

https://github.com/vectozavr/llm-hessian

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Hessian of Perplexity for Large Language Models by PyTorch autograd (Open Source)

https://github.com/vectozavr/thanos

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Thanos: A Block-wise Pruning Algorithm for Efficient Large Language Model Compression

https://github.com/venkatasg/lil-bevo

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Lil-Bevo: Explorations of Strategies for Training Language Models in More Humanlike Ways

https://github.com/venkatasg/multilingual-counterfactual-probing

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Counterfactually Probing Language Identity in Multilingual Models

https://github.com/verdurechen/sos-retrieval-loop

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Spiral of Silence: How is Large Language Model Killing Information Retrieval? -- A Case Study on Open Domain Question Answering

https://github.com/vered1986/self_talk

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Unsupervised Commonsense Question Answering with Self-Talk

https://github.com/veronica320/wikihow-gosc

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Goal-Oriented Script Construction

https://github.com/veronicium/codebenchgen

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CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks

https://github.com/vevake/DomainAware_DST

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Domain-Aware Dialogue State Tracker for Multi-Domain Dialogue Systems

https://github.com/vhellendoorn/code-lms

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A Systematic Evaluation of Large Language Models of Code

https://github.com/via-research/vtrain

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vTrain: A Simulation Framework for Evaluating Cost-effective and Compute-optimal Large Language Model Training

https://github.com/vicentvankor/sun-shine

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Sun-Shine: A Large Language Model for Tibetan Culture

https://github.com/vicgalle/configurable-safety-tuning

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Configurable Safety Tuning of Language Models with Synthetic Preference Data

https://github.com/vicgalle/meta-self-critique

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MetaSC: Test-Time Safety Specification Optimization for Language Models

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

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

https://github.com/vicky-wil/monitor

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Assessing the Reliability of Large Language Model Knowledge

https://github.com/vicmak/ProofSeer

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Language Models with Pre-Trained (GloVe) Word Embeddings

https://github.com/victor-wang-902/surealm

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Suffix Retrieval-Augmented Language Modeling

https://github.com/victor7246/transject

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Manifold-Preserving Transformers are Effective for Short-Long Range Encoding

https://github.com/victordibia/neuralqa

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NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets

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