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20232025
most citedA Review of Nine Physics Engines for Reinforcement Learning Research

3 citations · 4 across the 9 of their papers we have counts for

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7 papers · 1 filter

cs.CL2025

Pixels to Principles: Probing Intuitive Physics Understanding in Multimodal Language Models

Mohamad Ballout, Serwan Jassim, Elia Bruni

This paper presents a systematic evaluation of state-of-the-art multimodal large language models (MLLMs) on intuitive physics tasks using the GRASP and IntPhys 2 datasets. We asses…

cs.CL2025

iVISPAR -- An Interactive Visual-Spatial Reasoning Benchmark for VLMs

Julius Mayer, Mohamad Ballout, Serwan Jassim +2

Vision-Language Models (VLMs) are known to struggle with spatial reasoning and visual alignment. To help overcome these limitations, we introduce iVISPAR, an interactive multimodal…

cs.CL2024

Interpretability of Language Models via Task Spaces

Lucas Weber, Jaap Jumelet, Elia Bruni +1

The usual way to interpret language models (LMs) is to test their performance on different benchmarks and subsequently infer their internal processes. In this paper, we present an…

cs.CL2024

From Form(s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense Consistency

Xenia Ohmer, Elia Bruni, Dieuwke Hupkes

The staggering pace with which the capabilities of large language models (LLMs) are increasing, as measured by a range of commonly used natural language understanding (NLU) benchma…

cs.CL2023★ 1 cited

The ICL Consistency Test

Lucas Weber, Elia Bruni, Dieuwke Hupkes

Just like the previous generation of task-tuned models, large language models (LLMs) that are adapted to tasks via prompt-based methods like in-context-learning (ICL) perform well…

cs.CL2023

GRASP: A novel benchmark for evaluating language GRounding And Situated Physics understanding in multimodal language models

Serwan Jassim, Mario Holubar, Annika Richter +3

This paper presents GRASP, a novel benchmark to evaluate the language grounding and physical understanding capabilities of video-based multimodal large language models (LLMs). This…

cs.CL2023

Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning

Lucas Weber, Elia Bruni, Dieuwke Hupkes

Finding the best way of adapting pre-trained language models to a task is a big challenge in current NLP. Just like the previous generation of task-tuned models (TT), models that a…