Amin Seffo, Aladin Djuhera, Masataro Asai, Holger Boche · Jun 4, 2025 · Citations: 0
Simulation Env MathCoding
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← Back to explorer "Don't Do That!": Guiding Embodied Systems through Large Language Model-based Constraint Generation Beyond Single-Turn: A Survey on Multi-Turn Interactions with Large Language Models MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts Multi-agent deep reinforcement learning with centralized training and decentralized execution for transportation infrastructure management
Tag: Math
Requires mathematical reasoning expertise in evaluation or annotation.
Papers in tag: 103
Research Utility Snapshot
Evaluation Modes
- Automatic Metrics (2)
- Simulation Env (2)
Human Feedback Types
- Red Team (1)
Required Expertise
- Math (4)
- Coding (1)
Yubo Li, Xiaobin Shen, Xinyu Yao, Xueying Ding, Yidi Miao, Ramayya Krishnan · Apr 7, 2025 · Citations: 0
Red Team Automatic Metrics Math
- We organize existing benchmarks and datasets into coherent categories reflecting the evolving landscape of multi-turn dialogue evaluation, and review a broad spectrum of enhancement methodologies, including model-centric strategies (in-cont
Hao Liang, Linzhuang Sun, Minxuan Zhou, Zirong Chen, Meiyi Qiang, Mingan Lin · Aug 14, 2024 · Citations: 0
Automatic Metrics Math
- While existing benchmarks such as MathVista and MathVerse have advanced the evaluation of multimodal math proficiency, they primarily rely on digitally rendered content and fall short in capturing the complexity of real-world scenarios.
- To bridge this gap, we introduce MathScape, a novel benchmark focused on assessing MLLMs' reasoning ability in realistic mathematical contexts.
M. Saifullah, K. G. Papakonstantinou, A. Bhattacharya, S. M. Stoffels, C. P. Andriotis · Jan 23, 2024 · Citations: 0
Simulation Env Math
- To tackle the high dimensionality of state and action spaces, we propose DDMAC-CTDE, a Deep Decentralized Multi-Agent Actor-Critic (DDMAC) reinforcement learning architecture with Centralized Training and Decentralized Execution (CTDE).
- To demonstrate the utility of the proposed framework, we also develop a new comprehensive benchmark environment representing an existing transportation network in Virginia, U.S., with heterogeneous pavement and bridge assets undergoing nons