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Research & Development
MOLERR2FIX: A New Benchmark for Evaluating AI Trustworthiness in Chemistry
TLDR: MOLERR2FIX is a novel benchmark designed to assess the trustworthiness of Large Language Models (LLMs) in chemistry by evaluating their ability to detect,...
Research & Development
Unlocking Human Cognition: How AI Models Learn from Real-World Environments
TLDR: A new computational framework, Ecologically Rational Meta-learned Inference (ERMI), uses large language models (LLMs) to generate realistic cognitive tasks and meta-learning to derive...
Research & Development
The Physical AI Revolution: Policy Gaps and Urgent Actions for Embodied AI
TLDR: The research paper "Embodied AI: Emerging Risks and Opportunities for Policy Action" highlights the rapid advancement of Embodied AI (EAI) – AI systems...
Research & Development
Automating Knowledge Representation in Software Engineering with LLMs
TLDR: This paper introduces an LLM-assisted workflow for automated ontology generation from software engineering standards. It focuses on relation triplet extraction, using open-source LLMs...
Research & Development
Mamba Models Outperform Transformers in Scaling Legal AI for Long Documents
TLDR: A new research paper benchmarks Mamba, a state-space model, against Transformer architectures for legal AI tasks like statutory classification and case law retrieval....
Research & Development
Waste-Bench: A New Benchmark Reveals VLLM Challenges in Real-World Waste Classification
TLDR: The research paper introduces Waste-Bench, a novel benchmark dataset designed to evaluate Vision Large Language Models (VLLMs) in complex, cluttered waste classification environments...