Papers with environmental complexity

3 papers
Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environments (2024.emnlp-main)

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Challenge: Large language models (LLMs) are generalist agents capable of operating within complex environments.
Approach: They propose a class of tools that can serve as a middleware layer shielding LLMs from environmental complexity.
Outcome: The proposed tool can shield the LLM from environmental complexity in two representative complex environments.
Ready Jurist One: Benchmarking Language Agents for Legal Intelligence in Dynamic Environments (2026.acl-long)

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Challenge: Existing benchmarks for legal intelligence are limited to static evaluation paradigms or simplified scenarios.
Approach: They introduce J1-ENVS, the first interactive and dynamic legal environment tailored for LLM-based agents.
Outcome: The proposed framework assesses task performance and procedural compliance across legal proficiency levels.
M2PA: A Multi-Memory Planning Agent for Open Worlds Inspired by Cognitive Theory (2025.findings-acl)

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Challenge: Open-world planning poses a challenge due to complex environments and task diversity . recent work shows that large language models (LLMs) lack the ability to connect to agents' experiences .
Approach: They propose an open-world multi-memory planning agent that combines large language models with human-like multi-mesh systems to leverage their strengths.
Outcome: The proposed agent outperforms state-of-the-art agents on 50 Minecraft tasks in zero-shot learning.

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