1 citations · 1 across the 6 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
cs.MA2025
Who Gets the Reward & Who Gets the Blame? Evaluation-Aligned Training Signals for Multi-LLM Agents
Chih-Hsuan, Yang, Tanwi Mallick +5
Large Language Models (LLMs) in multi-agent systems (MAS) have shown promise for complex tasks, yet current training methods lack principled ways to connect system-level evaluation…
cs.AI2025
Evaluating the Safety and Skill Reasoning of Large Reasoning Models Under Compute Constraints
Adarsha Balaji, Le Chen, Rajeev Thakur +2
Test-time compute scaling has demonstrated the ability to improve the performance of reasoning language models by generating longer chain-of-thought (CoT) sequences. However, this…