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20242026
most citedLarge Language Models for Planning: A Comprehensive and Systematic Survey

2 citations · 2 across the 9 of their papers we have counts for

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cs.CL2025

Agent-RewardBench: Towards a Unified Benchmark for Reward Modeling across Perception, Planning, and Safety in Real-World Multimodal Agents

Tianyi Men, Zhuoran Jin, Pengfei Cao +3

As Multimodal Large Language Models (MLLMs) advance, multimodal agents show promise in real-world tasks like web navigation and embodied intelligence. However, due to limitations i…