8 papers
Beyond the Hivemind: Escaping LLM Homogeneity via Meta-Persona Anchoring and Sequential Temperature Scaling
Tairan Fu, Javier Conde, Carlos Arriaga +5
Recent studies have identified an ``Artificial Hivemind'' effect in Large Language Models (LLMs) causing models to converge on a narrow, homogenized consensus even for open questio…
Lost in Sampling: Assessing Lexical Reachability in LLMs via the Word Coverage Score (WCS)
Samer Awad, Javier Conde, Carlos Arriaga +4
Modern Large Language Models (LLMs) are often criticized for producing repetitive and homogeneous text, despite possessing vast latent vocabularies. While previous research has foc…
To Words and Beyond: Probing Large Language Models for Sentence-Level Psycholinguistic Norms of Memorability and Reading Times
Thomas Hikaru Clark, Carlos Arriaga, Javier Conde +2
Large Language Models (LLMs) have recently been shown to produce estimates of psycholinguistic norms, such as valence, arousal, or concreteness, for words and multiword expressions…
Beyond Reproducibility: Token Probabilities Expose Large Language Model Nondeterminism
Tairan Fu, Gonzalo MartÃnez, Javier Conde +4
The execution of Large Language Models (LLMs) has been shown to produce nondeterministic results when run on Graphics Processing Units (GPUs), even when they are configured to prod…
Assessing Latency in ASR Systems: A Methodological Perspective for Real-Time Use
Carlos Arriaga, Alejandro Pozo, Javier Conde +1
Automatic speech recognition (ASR) systems generate real-time transcriptions but often miss nuances that human interpreters capture. While ASR is useful in many contexts, interpret…
Adding LLMs to the psycholinguistic norming toolbox: A practical guide to getting the most out of human ratings
Javier Conde, MarÃa Grandury, Tairan Fu +7
Word-level psycholinguistic norms lend empirical support to theories of language processing. However, obtaining such human-based measures is not always feasible or straightforward.…