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Notes on large language model
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SkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplaces
The paper presents SkillFuzz, a method for discovering unintended objectives (implicit intents) in Large Language Model (LLM)-based agents that use reusable skills from open skill marketplaces. SkillFuzz works by…
Autonomous Scientific Discovery via Iterative Meta-Reflection
Researchers present DiscoPER, a framework for autonomous scientific discovery using large language models. It can explore datasets without predefined research objectives, conduct statistical testing to ensure validity…
Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian
Researchers investigated cross-lingual relation extraction for Romanian using large language models (LLMs) and an English to Romanian translation pipeline. They evaluated a 31B LLM under different configurations…
Weave of Formal Thought
The paper introduces Weave of Formal Thought (WoFT), a new paradigm for large language models that combines syntactic validation with learned structural representations. The proposed approach includes a formal engine…
GIF: Locally Sound Geometric Information Flow Control for LLMs
Researchers present a new framework called Geometric Information Flow (GIF) for tracking information flow from input tokens to outputs in large language models. This framework uses the Jacobian and local output…
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