Compact BERT-Based Multi-Models for Efficient Fake News Detection

Rana, Vineet; Garg, Vyom; Mago, Yatharth; Bhat, Aruna

doi:10.1109/conit59222.2023.10205773

Cited by 2 publications

(1 citation statement)

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“…The issue of computational efficiency is pivotal; thus, the model postulates the potential utility of smaller, specialized models for specific modules. For example, less computationally demanding pre-trained models, such as BERT-Tiny and BERT-Small, if fine-tuned appropriately, could outperform a larger, general-purpose model like GPT-4 in specialized tasks (Rana et al, 2023). The crux of the model resides in the executive function module, a computational entity that ensures mental cohesion and preserves a unified sense of self.…”

Section: The Proposed Model: Autonomous Agents As Proxies For Mental ...mentioning

confidence: 99%

Synthesizing Sentience: Integrating Large Language Models and Autonomous Agents for Emulating Human Cognitive Complexity

Ratican,

Hutson,

Plate

2023

JAIMLD

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The paper aims to present a novel methodology for emulating the intricacies of human cognitive complexity by ingeniously integrating large language models with autonomous agents. Grounded in the theoretical framework of the modular mind theory-originally espoused by Fodor and later refined by scholars such as Joanna Bryson-the study seeks to venture into the untapped potential of large language models and autonomous agents in mirroring human cognition. Recent advancements in artificial intelligence, exemplified by the inception of autonomous agents like Age in GPT, auto GPT, and baby AGI, underscore the transformative capacities of these technologies in diverse applications. Moreover, empirical studies have substantiated that persona-driven autonomous agents manifest enhanced efficacy and nuanced performance, mimicking the intricate dynamics of human interactions. The paper postulates a theoretical framework incorporating persona-driven modules that emulate psychological functions integral to general cognitive processes. This framework advocates for the deployment of a plurality of autonomous agents, each informed by specific large language models, to act as surrogates for different cognitive functionalities. Neurological evidence is invoked to bolster the theoretical architecture, delineating how autonomous agents can serve as efficacious proxies for modular cognitive centers within the human brain. Given this foundation, a theory of mind predicated upon modular constructs offers a fertile landscape for further empirical investigations and technological innovations.

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Section: The Proposed Model: Autonomous Agents As Proxies For Mental ...mentioning

confidence: 99%