Imagination is All You Need! Curved Contrastive Learning for Abstract Sequence Modeling Utilized on Long Short-Term Dialogue Planning

Inspired by the curvature of space-time (Einstein, 1921), we introduce Curved Contrastive Learning (CCL), a novel representation learning technique for learning the relative turn distance between utterance pairs in multi-turn dialogues. The resulting bi-encoder models can guide transformers as a response ranking model towards a goal in a zero-shot fashion by projecting the goal utterance and the corresponding reply candidates into a latent space. Here the cosine similarity indicates the distance/reachability of a candidate utterance toward the corresponding goal. Furthermore, we explore how these forward-entailing language representations can be utilized for assessing the likelihood of sequences by the entailment strength i.e. through the cosine similarity of its individual members (encoded separately) as an emergent property in the curved space. These non-local properties allow us to imagine the likelihood of future patterns in dialogues, specifically by ordering/identifying future goal utterances that are multiple turns away, given a dialogue context. As part of our analysis, we investigate characteristics that make conversations (un)plannable and find strong evidence of planning capability over multiple turns (in 61.56% over 3 turns) in conversations from the DailyDialog (Li et al., 2017) dataset. Finally, we show how we achieve higher efficiency in sequence modeling tasks compared to previous work thanks to our relativistic approach, where only the last utterance needs to be encoded and computed during inference.Comment: Accepted in ACL 2023 Finding

Reversible Metal-Free Carbon Dioxide Binding by Frustrated Lewis Pairs

Frustrated Lewis pairs comprising phosphine and borane react to reversibly bind and release CO2, offering a rare example of metal-free CO2 sequestration. The mechanism of formation of CO2 derivatives by almost simultaneous P-C and O-B bond formation was characterized by quantum chemical calculations

New insights into frustrated Lewis pairs: structural investigations of intramolecular phosphane-borane adducts by using modern solid-state NMR techniques and DFT calculations

Covalent bonding interactions between the Lewis acid and Lewis base functionalities have been probed in a series of “frustrated Lewis pairs” (FLPs) (mainly substituted vinylene linked intramolecular phosphane–borane adducts), using solid-state nuclear magnetic resonance techniques and accompanying DFT calculations. Both the 11B NMR isotropic chemical shifts and nuclear electric quadrupolar coupling parameters turn out to be extremely sensitive experimental probes for such interactions, revealing linear correlations with boron–phosphorus internuclear distances. The principal component Vzz of the 11B electric field gradient tensor is tilted slightly away (∼20°) from the boron–phosphorus internuclear vector, leading to an improved understanding of the remarkable reactivity of the FLPs. Complementary 31P{1H}-CPMAS experiments reveal significant 31P–11B scalar spin–spin interactions (1J ≈ 50 Hz), evidencing covalent bonding interactions between the reaction centers. Finally, 11B{31P} rotational echo double resonance (REDOR) experiments show systematic deviations from calculated curves based on the internuclear distances from X-ray crystallography. These deviations suggest non-zero contributions from anisotropic indirect spin–spin (J anisotropy) interactions, thereby offering additional evidence for covalent bonding.SFB 858 “Cooperative Systems in Chemistry”Fonds der Chemischen IndustrieNRW Forschungsschule “Molecules and Materials

Physics and information: what is the role of information in physics?

More than a century ago, physicists around the world were collectively developing a theory to describe the newly discovered strange behaviours of some physical systems. This marks the birth of quantum theory. Few decades later, the groundbreaking idea to separate information from its physical carrier led to the establishment of information theory. These, initially independent theories, merged together in the last decades of the former century, leaving us with quantum information theory. This thesis will explore topics at the intersection of mathematics, physics and computer science, trying to elucidate the interwovenness of these three disciplines. While doing so, the results that were established during the years of studies leading up to this work are introduced. The question posed in the title will not be answered fully, as it may be too early still to give a definite answer to this multifaceted question

In-Orbit Analysis of Antenna Pattern Anomalies of GNSS Satellites

The payload of a typical navigation satellite encounters heavy strains during launch. This indicates the need to characterize and assess the antenna and consequently the total signal performance of a satellite in orbit. Using ground measurements with a high gain antenna seems to be a powerful basis for this analysis. This paper introduces the used measurement facility and strategies for obtaining a sufficient amount of measurement data based on the used simplified satellite attitude and yaw steering model. The analysis algorithms will be described in detail and as a side product itwill be shown that transmitter power variations of the navigation satellite over time can be characterized and separated from the pure influence of the satellite antenna. The last section presents the exemplary antenna pattern characterization for the second Galileo test satellite GIOVE-B (Galileo In-Orbit Validation Element) based on calibrated flux density measurements taken with DLR’s 30 m high gain antenna for the E1 frequency band