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Green AI & Sustainable Compute 28 Feb 2026

Towards Autonomous Memory Agents

arXiv:2602.22406v1 Announce Type: new Abstract: Recent memory agents improve LLMs by extracting experiences and conversation history into an external storage. This enables low-overhead context assembly and online memory update without expensive LLM training. However, existing sol

By Xinle Wu, Rui Zhang, Mustafa Anis Hussain, Yao Lu arXiv cs.AI
Green AI & Sustainable Compute 28 Feb 2026

Vibe Researching as Wolf Coming: Can AI Agents with Skills Replace or Augment Social Scientists?

arXiv:2602.22401v1 Announce Type: new Abstract: AI agents -- systems that execute multi-step reasoning workflows with persistent state, tool access, and specialist skills -- represent a qualitative shift from prior automation technologies in social science. Unlike chatbots that r

By Yongjun Zhang arXiv cs.AI
Green AI & Sustainable Compute 28 Feb 2026

Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents

arXiv:2602.22302v1 Announce Type: new Abstract: Traditional software relies on contracts -- APIs, type systems, assertions -- to specify and enforce correct behavior. AI agents, by contrast, operate on prompts and natural language instructions with no formal behavioral specificat

By Varun Pratap Bhardwaj arXiv cs.AI
Green AI & Sustainable Compute 28 Feb 2026

Multi-Level Causal Embeddings

arXiv:2602.22287v1 Announce Type: new Abstract: Abstractions of causal models allow for the coarsening of models such that relations of cause and effect are preserved. Whereas abstractions focus on the relation between two models, in this paper we study a framework for causal emb

By Willem Schooltink, Fabio Massimo Zennaro arXiv cs.AI
Green AI & Sustainable Compute 28 Feb 2026

FIRE: A Comprehensive Benchmark for Financial Intelligence and Reasoning Evaluation

arXiv:2602.22273v1 Announce Type: new Abstract: We introduce FIRE, a comprehensive benchmark designed to evaluate both the theoretical financial knowledge of LLMs and their ability to handle practical business scenarios. For theoretical assessment, we curate a diverse set of exam

By Xiyuan Zhang, Huihang Wu, Jiayu Guo, Zhenlin Zhang, Yiwei Zhang, Liangyu Huo, Xiaoxiao Ma, Jiansong Wan, Xuewei Jiao, Yi Jing, Jian Xie arXiv cs.AI
Green AI & Sustainable Compute 28 Feb 2026

Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation

arXiv:2602.22215v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate potential in the field of scientific idea generation. However, the generated results often lack controllable academic context and traceable inspiration pathways. To bridge this gap, this pape

By Pengzhen Xie, Huizhi Liang arXiv cs.AI
Policy, Regulation & Markets 25 Feb 2026

Over a billion fear losing land and homes within five years

Despite global progress in strengthening land tenure and governance, more than a billion people worldwide – nearly one in four adults – fear they could lose the rights to some or all of their land and housing within the next five years.

UN News - Climate Change
Climate Tech & Infrastructure 24 Feb 2026

More trees where they matter, please

An international study reveals disparities in urban shade levels, exacerbating the “heat island” effect in big cities.

By Peter Dizikes | MIT News MIT News - Climate

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