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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/larspars/word-rnn

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Shifting Mean Activation Towards Zero with Bipolar Activation Functions

https://github.com/lasmp23/lasmp

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LASMP: Language Aided Subset Sampling Based Motion Planner

https://github.com/launchnlp/PROF

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Closing the Loop: Learning to Generate Writing Feedback via Language Model Simulated Student Revisions

https://github.com/launchnlp/actcab

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Enhancing Language Model Factuality via Activation-Based Confidence Calibration and Guided Decoding

https://github.com/launchnlp/litcab

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LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses

https://github.com/launchnlp/lito

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Enhanced Language Model Truthfulness with Learnable Intervention and Uncertainty Expression

https://github.com/lava-lab/cool-mc

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Enhancing RL Safety with Counterfactual LLM Reasoning

https://github.com/lavender105/rsgpt

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RSGPT: A Remote Sensing Vision Language Model and Benchmark

https://github.com/laytextllm/laytextllm

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A Bounding Box is Worth One Token: Interleaving Layout and Text in a Large Language Model for Document Understanding

https://github.com/lazizcodes/twicing_attention

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Transformer Meets Twicing: Harnessing Unattended Residual Information

https://github.com/lazychih114/AgentGen-Reproduction

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AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation

https://github.com/lbcb-sci/rinalmo

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RiNALMo: General-Purpose RNA Language Models Can Generalize Well on Structure Prediction Tasks

https://github.com/lbotirx/cofipara

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CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models

https://github.com/lbox-kr/nestle

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NESTLE: a No-Code Tool for Statistical Analysis of Legal Corpus

https://github.com/lbynum/sequence-driven-scms

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Language Models as Causal Effect Generators

https://github.com/lclm-horizon/a-comprehensive-survey-for-long-context-language-modeling

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A Comprehensive Survey on Long Context Language Modeling

https://github.com/lcs2-iiitd/code-mixed-classification

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A Comprehensive Understanding of Code-mixed Language Semantics using Hierarchical Transformer

https://github.com/ldong1111/graphemebert

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Neural Grapheme-to-Phoneme Conversion with Pre-trained Grapheme Models

https://github.com/ldos-project/tracellm

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Large Language Models as Realistic Microservice Trace Generators

https://github.com/ldzhangyx/bart-fusion

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Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model

https://github.com/ldzhangyx/loop-copilot

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Loop Copilot: Conducting AI Ensembles for Music Generation and Iterative Editing

https://github.com/leaperovo/adaptivelog-review

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AdaptiveLog: An Adaptive Log Analysis Framework with the Collaboration of Large and Small Language Model

https://github.com/learning-at-home/hivemind

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Distributed Deep Learning in Open Collaborations

https://github.com/leaves162/cliptrase

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Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation

https://github.com/leduckhai/litegpt

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LiteGPT: Large Vision-Language Model for Joint Chest X-ray Localization and Classification Task

https://github.com/leeeeoliu/llm-crs

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Conversational Recommender System and Large Language Model Are Made for Each Other in E-commerce Pre-sales Dialogue

https://github.com/leeyn-43/clover

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Clover: Towards A Unified Video-Language Alignment and Fusion Model

https://github.com/leezekun/dialogic

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Controllable Dialogue Simulation with In-Context Learning

https://github.com/leezythu/focusllm

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FocusLLM: Precise Understanding of Long Context by Dynamic Condensing

https://github.com/lefameuxbeding/learned_aggregation

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Can We Learn Communication-Efficient Optimizers?

https://github.com/lehengthu/alpharec

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Language Representations Can be What Recommenders Need: Findings and Potentials

https://github.com/leia-llm/leia

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LEIA: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation

https://github.com/leililab/de-cop

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DE-COP: Detecting Copyrighted Content in Language Models Training Data

https://github.com/leililab/infinisst

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InfiniSST: Simultaneous Translation of Unbounded Speech with Large Language Model

https://github.com/lemonsis/association

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Improve Language Model and Brain Alignment via Associative Memory

https://github.com/lemuria-wchen/DialogVED

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DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation

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