2 papers
cs.CL2026
T1-Bench: Benchmarking Multi-Scenario Agents in Real-World Domains
Genta Indra Winata, Amartya Chakraborty, Yuzhen Lin +12
Recent advances in reasoning and tool-calling capabilities of large language models (LLMs) have enabled increasingly capable agentic systems. However, existing benchmarks remain li…
cs.CV2025
GETReason: Enhancing Image Context Extraction through Hierarchical Multi-Agent Reasoning
Shikhhar Siingh, Abhinav Rawat, Chitta Baral +1
Publicly significant images from events hold valuable contextual information, crucial for journalism and education. However, existing methods often struggle to extract this relevan…