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ResearchFormerly WizWand

Hallucination Evaluation on HallB

54.2ScoreSAIL
15.61625.63335.6545.667Oct 16, 2025
Updated 8mo ago

Evaluation results

MethodLinks
SAILLLM=Mistral-7B, # Data=512M / 86M / 6M, Model Scale=8B, Architecture Category=Native, Reinforcement Learning=false2025.1054.2
Qwen2.5-VLLLM=Qwen2.5-7B, # Data=- / - / -, Model Scale=8B, Architecture Category=Modular, Reinforcement Learning=true2025.1052.9
Encoder-BasedLLM=Qwen3-8B, # Data=>6B / 40M / 4M, Model Scale=8B, Architecture Category=Modular, Reinforcement Learning=false2025.1051.4
Qwen2-VLLLM=Qwen2-7B, # Data=- / - / -, Model Scale=8B, Architecture Category=Modular, Reinforcement Learning=false2025.1050.6
InternVL2.5LLM=InternLM2.5-7B, # Data=>6B / 50M / 4M, Model Scale=8B, Architecture Category=Modular, Reinforcement Learning=false2025.1050.1
InternVL3LLM=Qwen2.5-7B, # Data=>6B / 100M / 22M, Model Scale=8B, Architecture Category=Modular, Reinforcement Learning=true2025.1049.9
NEOLLM=Qwen3-8B, # Data=345M / 40M / 4M, Model Scale=8B, Architecture Category=Native, Reinforcement Learning=false2025.1046.4
Qwen2.5-VLLLM=Qwen2.5-3B, # Data=- / - / -, Model Scale=2B, Architecture Category=Modular, Reinforcement Learning=true2025.1046.3
Encoder-BasedLLM=Qwen3-1.7B, # Data=>6B / 40M / 4M, Model Scale=2B, Architecture Category=Modular, Reinforcement Learning=false2025.1044.4
NEOLLM=Qwen3-1.7B, # Data=345M / 40M / 4M, Model Scale=2B, Architecture Category=Native, Reinforcement Learning=false2025.1043.1
InternVL2.5LLM=InternLM2.5-1.8B, # Data=>6B / 100M / 16M, Model Scale=2B, Architecture Category=Modular, Reinforcement Learning=false2025.1042.6
InternVL3LLM=Qwen2.5-1.5B, # Data=>6B / 100M / 22M, Model Scale=2B, Architecture Category=Modular, Reinforcement Learning=true2025.1042.5
Qwen2-VLLLM=Qwen2-1.5B, # Data=- / - / -, Model Scale=2B, Architecture Category=Modular, Reinforcement Learning=false2025.1041.7
HoVLELLM=InternLM2-1.8B, # Data=550M / 50M / 7M, Model Scale=2B, Architecture Category=Native, Reinforcement Learning=false2025.1038.4
BREENLLM=Qwen2.5-7B, # Data=13M / 0M / 4M, Model Scale=8B, Architecture Category=Native, Reinforcement Learning=false2025.1037
Mono-InternVLLLM=InternLM2-1.8B, # Data=1.2B / 143M / 7M, Model Scale=2B, Architecture Category=Native, Reinforcement Learning=false2025.1034.8
Mono-InternVL-1.5LLM=InternLM2-1.8B, # Data=400M / 150M / 7M, Model Scale=2B, Architecture Category=Native, Reinforcement Learning=false2025.1032.5
EVELLM=Vicuna-7B, # Data=33M / 0M / 1.8M, Model Scale=8B, Architecture Category=Native, Reinforcement Learning=false2025.1026.4
ChameleonLLM=from scratch, # Data=1.4B / 0M / 1.8M, Model Scale=8B, Architecture Category=Native, Reinforcement Learning=false2025.1017.1