2 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
An Emergent Mirage: Is Emergent Misalignment and Realignment Indeed a Robust Phenomenon?
Abhinav Rao, Liancheng Gong, Bin Hu +1
Recent work has reported Emergent Misalignment (EM), where language models fine-tuned on narrow, domain-specific misaligned datasets abruptly acquire broadly misaligned behavior, a…
How LLMs Comprehend Temporal Meaning in Narratives: A Case Study in Cognitive Evaluation of LLMs
Karin de Langis, Jong Inn Park, Andreas Schramm +5
Large language models (LLMs) exhibit increasingly sophisticated linguistic capabilities, yet the extent to which these behaviors reflect human-like cognition versus advanced patter…
Strong Memory, Weak Control: An Empirical Study of Executive Functioning in LLMs
Karin de Langis, Jong Inn Park, Bin Hu +5
Working memory, or the ability to hold and manipulate information in the mind, is a critical component of human intelligence and executive functioning. It is correlated with perfor…
Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation
Ruixin Yang, Dheeraj Rajagopal, Shirley Anugrah Hayati +2
Uncertainty estimation is a significant issue for current large language models (LLMs) that are generally poorly calibrated and over-confident, especially with reinforcement learni…
Under the Surface: Tracking the Artifactuality of LLM-Generated Data
Debarati Das, Karin De Langis, Anna Martin-Boyle +14
This work delves into the expanding role of large language models (LLMs) in generating artificial data. LLMs are increasingly employed to create a variety of outputs, including ann…