VisDocAgentBench / benchmark /topics.json
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[
{
"topic_id": "t01_embodied_world_models",
"topic_name": "Embodied World Models / World Action Models"
},
{
"topic_id": "t02_gui_computer_use_agents",
"topic_name": "GUI / Computer-Use Agents"
},
{
"topic_id": "t03_software_engineering_code_agents",
"topic_name": "Software Engineering / Code Agents"
},
{
"topic_id": "t04_agent_memory_long_horizon",
"topic_name": "Agent Memory / Long-Horizon Context Management"
},
{
"topic_id": "t05_multimodal_rag_visual_documents",
"topic_name": "Multimodal RAG / Visually Rich Document Understanding"
},
{
"topic_id": "t06_test_time_scaling_reasoning",
"topic_name": "Test-Time Scaling / Inference-Time Reasoning"
},
{
"topic_id": "t07_video_generation_control",
"topic_name": "Video Generation / Controllable Video Diffusion"
},
{
"topic_id": "t08_3d_spatial_intelligence",
"topic_name": "3D / Spatial Intelligence for Multimodal Models"
},
{
"topic_id": "t09_efficient_inference_kv_cache",
"topic_name": "Efficient LLM/VLM Inference and KV-Cache Optimization"
},
{
"topic_id": "t10_scientific_foundation_models",
"topic_name": "Scientific Foundation Models / AI for Materials and Physical Sciences"
}
]