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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/livnlp/timeadapted-dcwe

공식 코드

Learning Dynamic Contextualised Word Embeddings via Template-based Temporal Adaptation

https://github.com/lixinze777/knowledge-aware-language-model-attribution

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Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution

https://github.com/lixsh6/tencent_wsdm_cup2023

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Pretraining De-Biased Language Model with Large-scale Click Logs for Document Ranking

https://github.com/liyichen-cly/pog

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Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs

https://github.com/liyucheng09/contamination_detector

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Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation

https://github.com/liyucheng09/latesteval

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LatestEval: Addressing Data Contamination in Language Model Evaluation through Dynamic and Time-Sensitive Test Construction

https://github.com/lizhaoliu-lec/cg-vlm

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Contrastive Vision-Language Alignment Makes Efficient Instruction Learner

https://github.com/lj2lijia/codeeditor

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CodeEditor: Learning to Edit Source Code with Pre-trained Models

https://github.com/ljy0ustc/llara

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LLaRA: Large Language-Recommendation Assistant

https://github.com/ljy0ustc/patchrec

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Multi-Grained Patch Training for Efficient LLM-based Recommendation

https://github.com/lliar-liar/daily-omni

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Daily-Omni: Towards Audio-Visual Reasoning with Temporal Alignment across Modalities

https://github.com/lliutianc/roselora

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RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning

https://github.com/llm-as-dataset-analyst/SSDLLM

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LLM as Dataset Analyst: Subpopulation Structure Discovery with Large Language Model

https://github.com/llm-conditioned-diffusion/llm-conditioned-diffusion.github.io

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An Empirical Study and Analysis of Text-to-Image Generation Using Large Language Model-Powered Textual Representation

https://github.com/llm4se/obfuscated-chatgpt-experiments

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Breaking the Silence: the Threats of Using LLMs in Software Engineering

https://github.com/llmkvsys/rethink-kv-compression

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Rethinking Key-Value Cache Compression Techniques for Large Language Model Serving

https://github.com/lm-pub-quiz/lm-pub-quiz

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BEAR: A Unified Framework for Evaluating Relational Knowledge in Causal and Masked Language Models

https://github.com/lmarena/p2l

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Prompt-to-Leaderboard

https://github.com/lmb-freiburg/locov

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Localized Vision-Language Matching for Open-vocabulary Object Detection

https://github.com/lmb-freiburg/ovqa

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Open-ended VQA benchmarking of Vision-Language models by exploiting Classification datasets and their semantic hierarchy

https://github.com/lmd0311/hermes

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HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation

https://github.com/lmgame-org/gamingagent

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lmgame-Bench: How Good are LLMs at Playing Games?

https://github.com/lmm101/awesome-multimodal-next-token-prediction

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Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey

https://github.com/lmous/openai-gpt4-coding-assistant

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OpenAi's GPT4 as coding assistant

https://github.com/lnikolenko/EQA

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When in Doubt, Ask: Generating Answerable and Unanswerable Questions, Unsupervised

https://github.com/lockon-n/dapo

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Dialogue-adaptive Language Model Pre-training From Quality Estimation

https://github.com/locuslab/deq

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Deep Equilibrium Models

https://github.com/locuslab/trellisnet

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Trellis Networks for Sequence Modeling

https://github.com/log-postech/safe-jax

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SAFE: Finding Sparse and Flat Minima to Improve Pruning

https://github.com/logintelligence/log-analytics-chatgpt

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Log Parsing: How Far Can ChatGPT Go?

https://github.com/lolya-cloud/adversarial-attacks-on-neural-text-detectors

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Efficient Black-Box Adversarial Attacks on Neural Text Detectors

https://github.com/longhao-chen/aicas2024

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Optimization of Armv9 architecture general large language model inference performance based on Llama.cpp

https://github.com/longrongyang/stgc

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Solving Token Gradient Conflict in Mixture-of-Experts for Large Vision-Language Model

https://github.com/loris3/evaluation_explanation_quality

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An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated Text

https://github.com/lostwolves/IFShip

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IFShip: Interpretable Fine-grained Ship Classification with Domain Knowledge-Enhanced Vision-Language Models

https://github.com/louaaron/score-entropy-discrete-diffusion

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Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

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