2 citations · 4 across the 4 of their papers we have counts for
6 papers · 1 filter
Comparing Human and Language Models Sentence Processing Difficulties on Complex Structures
Samuel Joseph Amouyal, Aya Meltzer-Asscher, Jonathan Berant
Large language models (LLMs) that fluently converse with humans are a reality - but do LLMs experience human-like processing difficulties? We systematically compare human and LLM s…
When the LM misunderstood the human chuckled: Analyzing garden path effects in humans and language models
Samuel Joseph Amouyal, Aya Meltzer-Asscher, Jonathan Berant
Modern Large Language Models (LLMs) have shown human-like abilities in many language tasks, sparking interest in comparing LLMs' and humans' language processing. In this paper, we…
GLEE: A Unified Framework and Benchmark for Language-based Economic Environments
Eilam Shapira, Omer Madmon, Itamar Reinman +3
Large Language Models (LLMs) show significant potential in economic and strategic interactions, where communication via natural language is often prevalent. This raises key questio…
AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?
Ori Yoran, Samuel Joseph Amouyal, Chaitanya Malaviya +3
Language agents, built on top of language models (LMs), are systems that can interact with complex environments, such as the open web. In this work, we examine whether such agents…
Large Language Models for Psycholinguistic Plausibility Pretesting
Samuel Joseph Amouyal, Aya Meltzer-Asscher, Jonathan Berant
In psycholinguistics, the creation of controlled materials is crucial to ensure that research outcomes are solely attributed to the intended manipulations and not influenced by ext…
STEER: Assessing the Economic Rationality of Large Language Models
Narun Raman, Taylor Lundy, Samuel Amouyal +3
There is increasing interest in using LLMs as decision-making "agents." Doing so includes many degrees of freedom: which model should be used; how should it be prompted; should it…