Abstract: This study proposes LiP-LLM: integrating linear programming and dependency graph with large language models (LLMs) for multi-robot task planning. For multi-robots to efficiently perform ...

OpenAI researchers have introduced a novel method that acts as a "truth serum" for large language models (LLMs), compelling them to self-report their own misbehavior, hallucinations and policy ...

ABSTRACT: This article examines some of the properties of quasi-Fejer sequences when used in quasi-gradiental techniques as an alternative to stochastic search techniques for optimizing unconstrained ...

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Linear Programs (LPs) are one of the major building blocks of AI and have championed recent strides in differentiable optimizers for learning systems. While efficient solvers exist for even ...

It is tough to remove bias, and in some cases, outright censorship, in large language models (LLMs). One such model, DeepSeek from China, alarmed politicians and some business leaders about its ...

ABSTRACT: This paper deals with linear programming techniques and their application in optimizing lecture rooms in an institution. This linear programming formulated based on the available secondary ...

Two Microsoft researchers have devised a new, optimization-free jailbreak method that can effectively bypass the safety mechanisms of most AI systems. Called Context Compliance Attack (CCA), the ...

In the realm of competitive programming, both human participants and artificial intelligence systems encounter a set of unique challenges. Many existing code generation models struggle to consistently ...