https://github.com/giannispana/ails-ntua-at-semeval-2024-task-9-brainteaser
BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
Papers with Code 아카이브
Large Language Model
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 2
- 평가표
- 0
- 보존된 평가 기록
- 0
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/gicheonkang/gst-visdial
https://github.com/goodevening13/aquakv
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
https://github.com/goodmike31/pl-asr-bigos-tools
https://github.com/google-deepmind/alphadev
https://github.com/greenbitai/low_bit_llama
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
https://github.com/gusye1234/nano-graphrag
From Local to Global: A Graph RAG Approach to Query-Focused Summarization
https://github.com/gzhu06/cacophony
https://github.com/hahnyuan/llmviewer
https://github.com/haiquanlu/alphapruning
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
https://github.com/hanguo97/flute
Pushing the Limits of Large Language Model Quantization via the Linearity Theorem
https://github.com/hazyresearch/flash-attention
Efficient Memory Management for Large Language Model Serving with PagedAttention
https://github.com/hazyresearch/legalbench
Learning to Generate Instruction Tuning Datasets for Zero-Shot Task Adaptation
https://github.com/heegyukim/open-korean-instructions
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
https://github.com/hemingkx/Spec-Bench
https://github.com/heyuan9/medscore
https://github.com/hieuphan33/cvpr2024_mavl
https://github.com/hitz-zentroa/eval-MCG-COLING-2025
A LLM-Based Ranking Method for the Evaluation of Automatic Counter-Narrative Generation
https://github.com/hitz-zentroa/lm-contamination
NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark
https://github.com/hitz-zentroa/whisper-lm-transformers
Whisper-LM: Improving ASR Models with Language Models for Low-Resource Languages
https://github.com/hiyouga/easyr1
https://github.com/hkuds/auto-deep-research
AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents
https://github.com/hodeld/emergent_analogies_llm_fork
https://github.com/huggingface/amused
Muse: Text-To-Image Generation via Masked Generative Transformers
https://github.com/huggingface/open-muse
Muse: Text-To-Image Generation via Masked Generative Transformers
https://github.com/humanmllm/r1-omni
R1-Omni: Explainable Omni-Multimodal Emotion Recognition with Reinforcement Learning
https://github.com/hzy312/knowledge-r1
Reinforced Internal-External Knowledge Synergistic Reasoning for Efficient Adaptive Search Agent
https://github.com/ibm-self-serve-assets/metagen-blended-rag
MetaGen Blended RAG: Higher Accuracy for Domain-Specific Q&A Without Fine-Tuning
https://github.com/ictnlp/streamspeech
Stream-Omni: Simultaneous Multimodal Interactions with Large Language-Vision-Speech Model
https://github.com/ieellee/ullsam
Unifying Segment Anything in Microscopy with Multimodal Large Language Model
https://github.com/illuin-tech/colpali
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/illuin-tech/vidore-benchmark
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/ilyagusev/ping_pong_bench
https://github.com/ilyagusev/rulm
Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data
https://github.com/inclusionai/aworld
RAG-R1 : Incentivize the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism
https://github.com/inspire-group/RobustRAG
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.