4 papers
PSALM-V: Automating Symbolic Planning in Interactive Visual Environments with Large Language Models
Wang Bill Zhu, Miaosen Chai, Ishika Singh +2
We propose PSALM-V, the first autonomous neuro-symbolic learning system able to induce symbolic action semantics (i.e., pre- and post-conditions) in visual environments through int…
Why Do Some Inputs Break Low-Bit LLM Quantization?
Ting-Yun Chang, Muru Zhang, Jesse Thomason +1
Low-bit weight-only quantization significantly reduces the memory footprint of large language models (LLMs), but disproportionately affects certain examples. We analyze diverse 3-4…
Large Language Models Do Multi-Label Classification Differently
Marcus Ma, Georgios Chochlakis, Niyantha Maruthu Pandiyan +2
Multi-label classification is prevalent in real-world settings, but the behavior of Large Language Models (LLMs) in this setting is understudied. We investigate how autoregressive…
Evaluating Creativity and Deception in Large Language Models: A Simulation Framework for Multi-Agent Balderdash
Parsa Hejabi, Elnaz Rahmati, Alireza S. Ziabari +3
Large Language Models (LLMs) have shown impressive capabilities in complex tasks and interactive environments, yet their creativity remains underexplored. This paper introduces a s…