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홈
SOTA
질문 응답
Question Answering On Webquestions
Question Answering On Webquestions
평가 지표
EM
평가 결과
이 벤치마크에서 각 모델의 성능 결과
Columns
모델 이름
EM
Paper Title
Repository
CoA
70.7
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
CoA w/o actions
64.7
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
DSP
59.4
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
DSP
59.4
DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines
FiE+PAQ
56.3
FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering
-
FiE
52.4
FiE: Building a Global Probability Space by Leveraging Early Fusion in Encoder for Open-Domain Question Answering
-
FiDO
51.1
FiDO: Fusion-in-Decoder optimized for stronger performance and faster inference
-
RAG
45.2
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Few-shot
44.7
Language Models are Few-Shot Learners
Few-shot
44.7
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
PaLM-540B (Few-Shot)
43.5
PaLM: Scaling Language Modeling with Pathways
Zero-shot
43
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
Zero-shot
43
Language Models are Unsupervised Multitask Learners
-
T5.1.1-XXL+SSM
42.8
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
CoT
42.5
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
CoT
42.5
Chain-of-Action: Faithful and Multimodal Question Answering through Large Language Models
DPR
42.4
Dense Passage Retrieval for Open-Domain Question Answering
GPT-3-175B (Few-Shot)
41.5
Language Models are Few-Shot Learners
REALM
40.7
REALM: Retrieval-Augmented Language Model Pre-Training
React
38.3
ReAct: Synergizing Reasoning and Acting in Language Models
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