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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/shark-nlp/openicl

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OpenICL: An Open-Source Framework for In-context Learning

https://github.com/shark0-0/vg4d

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VG4D: Vision-Language Model Goes 4D Video Recognition

https://github.com/sharonlevy/contextualquestions

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Evaluating Biases in Context-Dependent Health Questions

https://github.com/shawnhuang497/bird

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A Refer-and-Ground Multimodal Large Language Model for Biomedicine

https://github.com/shawnhuang497/medplib

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Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine

https://github.com/shawnkx/NAT-with-Local-AT

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Incorporating a Local Translation Mechanism into Non-autoregressive Translation

https://github.com/shawnricecake/agile-quant

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Agile-Quant: Activation-Guided Quantization for Faster Inference of LLMs on the Edge

https://github.com/shayankiyani98/cp

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Length Optimization in Conformal Prediction

https://github.com/sheikhshafayat/multi-fact

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Multi-FAct: Assessing Factuality of Multilingual LLMs using FActScore

https://github.com/shengnanh20/lamp

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LAMP: Leveraging Language Prompts for Multi-person Pose Estimation

https://github.com/shenshuaijie/SDN

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SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models

https://github.com/shentao-yang/preference_grounded_guidance

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Preference-grounded Token-level Guidance for Language Model Fine-tuning

https://github.com/shentianxiao/film

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FiLM: Fill-in Language Models for Any-Order Generation

https://github.com/shenxiaochenn/SongCi

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Large-vocabulary forensic pathological analyses via prototypical cross-modal contrastive learning

https://github.com/sheryc/resonance_rope

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Resonance RoPE: Improving Context Length Generalization of Large Language Models

https://github.com/shijian2001/templatematters

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Template Matters: Understanding the Role of Instruction Templates in Multimodal Language Model Evaluation and Training

https://github.com/shijxcs/candle

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Efficient and Long-Tailed Generalization for Pre-trained Vision-Language Model

https://github.com/shimisalant/CWR

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Contextualized Word Representations for Reading Comprehension

https://github.com/shinying/dest

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Learning Fine-Grained Visual Understanding for Video Question Answering via Decoupling Spatial-Temporal Modeling

https://github.com/shiranD/word_level_evaluation

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Are Some Words Worth More than Others?

https://github.com/shivank21/Implicit_Preference_Optimization

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IPO: Your Language Model is Secretly a Preference Classifier

https://github.com/shizhediao/davinci

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Write and Paint: Generative Vision-Language Models are Unified Modal Learners

https://github.com/shizhouxing/Attack-LM-Detectors

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Red Teaming Language Model Detectors with Language Models

https://github.com/shmsw25/Channel-LM-Prompting

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Noisy Channel Language Model Prompting for Few-Shot Text Classification

https://github.com/showlab/egovlp

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Egocentric Video-Language Pretraining @ EPIC-KITCHENS-100 Multi-Instance Retrieval Challenge 2022

https://github.com/showlab/movieseq

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Learning Video Context as Interleaved Multimodal Sequences

https://github.com/showlab/show-o

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Show-o2: Improved Native Unified Multimodal Models

https://github.com/showlab/videolisa

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One Token to Seg Them All: Language Instructed Reasoning Segmentation in Videos

https://github.com/shrango/poss

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POSS: Position Specialist Generates Better Draft for Speculative Decoding

https://github.com/shreyansh26/SRST-18

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IIT (BHU) Varanasi at MSR-SRST 2018: A Language Model Based Approach for Natural Language Generation

https://github.com/shtoshni/learning-chess-blindfolded

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Chess as a Testbed for Language Model State Tracking

https://github.com/shtoshni92/learning-chess-blindfolded

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Chess as a Testbed for Language Model State Tracking

https://github.com/shtuplus/iccc_cvpr2024

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Learning by Correction: Efficient Tuning Task for Zero-Shot Generative Vision-Language Reasoning

https://github.com/shuaizhao95/Unlearning

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Unlearning Backdoor Attacks for LLMs with Weak-to-Strong Knowledge Distillation

https://github.com/shuishen112/tensortrainlm

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Language Modeling Using Tensor Trains

https://github.com/shuklagroup/lazbfdef

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Substrate Prediction for RiPP Biosynthetic Enzymes via Masked Language Modeling and Transfer Learning

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