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This AI Paper Introduces Group Think: A Token-Level Multi-Agent Reasoning Paradigm for Faster and Collaborative LLM Inference

A prominent area of exploration involves enabling large language models (LLMs) to function collaboratively. Multi-agent...

This AI Paper from Microsoft Introduces WINA: A Training-Free Sparse Activation Framework for Efficient Large Language Model Inference

Large language models (LLMs), with billions of parameters, power many AI-driven services across industries. However...

Thinking with Many Minds: Using Large Language Models for Multi-Perspective Problem-Solving

arXiv:2501.02348v2 Announce Type: replace Abstract: Complex problem-solving requires cognitive flexibility–the capacity to entertain multiple perspectives...

Theorem-of-Thought: A Multi-Agent Framework for Abductive, Deductive, and Inductive Reasoning in Language Models

arXiv:2506.07106v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong performance across natural...

The World According to LLMs: How Geographic Origin Influences LLMs’ Entity Deduction Capabilities

arXiv:2508.05525v1 Announce Type: new Abstract: Large Language Models (LLMs) have been extensively tuned to mitigate...

The walled garden cracks: Nadella bets Microsoft’s Copilots—and Azure’s next act—on A2A/MCP interoperability

Microsoft CEO Satya Nadella’s endorsement of Google DeepMind‘s A2A open protocol and Anthropic’s MCP is...

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

arXiv:2510.08482v2 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive...

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