https://github.com/hanzhizhang-ulrica/dam
공식 코드DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference Acceleration
Papers with Code 아카이브
Language Modeling
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hao-ai-lab/vllm-ltr
공식 코드https://github.com/haochuan-mit/varaince-reduced-clipping-for-non-convex-optimization
공식 코드https://github.com/haodongze/self-ksel-qans
공식 코드Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question Answering
https://github.com/haofuml/cyclical_annealing
공식 코드Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing
https://github.com/haoqiu-yan/perceptiveagent
공식 코드Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction
https://github.com/haotian-liu/LLaVA
공식 코드Unified Modeling Language Code Generation from Diagram Images Using Multimodal Large Language Models
https://github.com/haoyiq114/valor
공식 코드VALOR-EVAL: Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models
https://github.com/haoyu-bu/CAFe
공식 코드CAFe: Unifying Representation and Generation with Contrastive-Autoregressive Finetuning
https://github.com/haozhe-an/sodapop
공식 코드SODAPOP: Open-Ended Discovery of Social Biases in Social Commonsense Reasoning Models
https://github.com/haozheji/exact-optimization
공식 코드Towards Efficient Exact Optimization of Language Model Alignment
https://github.com/haozhezhao/mic
공식 코드MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning
https://github.com/haozhg/lmd
공식 코드Language Model Decomposition: Quantifying the Dependency and Correlation of Language Models
https://github.com/happen2me/cross-gnn
공식 코드GraphextQA: A Benchmark for Evaluating Graph-Enhanced Large Language Models
https://github.com/harbecke/xbert
공식 코드Explaining Natural Language Processing Classifiers with Occlusion and Language Modeling
https://github.com/harmonic-discovery/pref-opt-for-mols
공식 코드https://github.com/harryjo97/rdlm
공식 코드https://github.com/harshp1802/text-dataset-distillation
공식 코드https://github.com/harvardnlp/BSO
공식 코드https://github.com/harvardnlp/NeuralSteganography
공식 코드https://github.com/harvardnlp/TextFlow
공식 코드https://github.com/harvardnlp/encoder-agnostic-adaptation
공식 코드Encoder-Agnostic Adaptation for Conditional Language Generation
https://github.com/harvardnlp/hmm-lm
공식 코드https://github.com/harvardnlp/urnng
공식 코드https://github.com/harvey-fin/icl-estimate
공식 코드Estimating Large Language Model Capabilities without Labeled Test Data
https://github.com/hasakixie123/llm-evaluator-uncertainty
공식 코드An Empirical Analysis of Uncertainty in Large Language Model Evaluations
https://github.com/hasan-rakibul/llmpathy
공식 코드Labels Generated by Large Language Model Helps Measuring People's Empathy in Vitro
https://github.com/hasanar1f/llava-hallunication-fix
공식 코드PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
https://github.com/hasanar1f/paint
공식 코드PAINT: Paying Attention to INformed Tokens to Mitigate Hallucination in Large Vision-Language Model
https://github.com/hassanhub/MultiGrounding
공식 코드Multi-level Multimodal Common Semantic Space for Image-Phrase Grounding
https://github.com/hawkrobe/continual-adaptation
공식 코드https://github.com/hayleypark/MorphologyMatters
공식 코드Morphology Matters: A Multilingual Language Modeling Analysis
https://github.com/hazyresearch/aioli
공식 코드Aioli: A Unified Optimization Framework for Language Model Data Mixing
https://github.com/hazyresearch/h3
공식 코드Hungry Hungry Hippos: Towards Language Modeling with State Space Models
https://github.com/hazyresearch/monarch
공식 코드Monarch: Expressive Structured Matrices for Efficient and Accurate Training
https://github.com/hazyresearch/safari
공식 코드Simple Hardware-Efficient Long Convolutions for Sequence Modeling
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.