LLM research

AI Agents

Seven-Dimensional Taxonomy Proposed for Healthcare AI Agents

New research proposes a comprehensive framework for empirically evaluating LLM-based agentic AI systems in healthcare, establishing seven key dimensions for systematic assessment.

LLM research

Knowledge Model Prompting Boosts LLM Planning Performance

New research introduces Knowledge Model Prompting, a technique that enhances LLM reasoning on complex planning tasks by structuring domain knowledge representation.

LLM research

Accordion-Thinking: A New Method for Efficient LLM Reasoning

New research introduces Accordion-Thinking, a self-regulated approach that compresses reasoning steps dynamically to improve LLM efficiency while maintaining readable chain-of-thought outputs.

AI sustainability

The Hidden Energy Cost of Saying 'Thank You' to AI

New research quantifies the surprising computational overhead of polite exchanges with AI chatbots, revealing how social niceties translate to real energy consumption.

LLM research

DAJ: Data-Reweighted LLM Judges Improve Code Generation

New research introduces DAJ, a data-reweighting approach for LLM judges that improves test-time scaling in code generation by better identifying correct solutions.

AI benchmarks

FrontierScience Benchmark Tests AI on Expert Science Tasks

New benchmark evaluates whether frontier AI models can perform PhD-level scientific research tasks, revealing significant gaps between current capabilities and expert human performance.

AI Safety

Research Explores How Information Access Shapes AI Sabotage Detec

New arXiv research investigates how varying levels of information access affect LLM monitors' ability to detect sabotage, with implications for AI safety and oversight systems.

LLM research

Policy of Thoughts: Evolving LLM Reasoning at Test Time

New research introduces test-time policy evolution to scale LLM reasoning without additional training, enabling models to dynamically improve their problem-solving strategies during inference.

LLM research

Small-Scale LLMs: Balancing AI Agent Performance with Sustainabil

New research explores how smaller language models can power AI agent systems while dramatically reducing computational costs and environmental impact without sacrificing capability.

LLM research

Process-Supervised RL: Precise Error Penalization Boosts LLM Reas

New research introduces a method to preserve correct reasoning steps while penalizing errors, improving LLM performance through more nuanced reinforcement learning credit assignment.

LLM research

Activation Steering: How Reasoning-Critical Neurons Improve LLM R

New research identifies specific neurons responsible for reasoning in LLMs and demonstrates how transferring their activation patterns can significantly improve inference reliability across models.

LLM research

Think-Augmented Function Calling Boosts LLM Parameter Accuracy

New research introduces embedded reasoning to improve how LLMs handle function parameters, addressing a critical bottleneck in AI agent reliability for tool-using applications.