On the role of dialogue models in the age of large language models.

We argue that Machine learning, in particular the currently prevalent generation of Large Language Models (LLMs), can work constructively with existing normative models of dialogue as exemplified by dialogue games, specifically their computational applications within, for example, inter-agent communication and automated dialogue management. Furthermore we argue that this relationship is bi-directional, that some uses of dialogue games benefit from increased functionality due to the specific capabilities of LLMs, whilst LLMs benefit from externalised models of, variously, problematic, normative, or idealised behaviour. Machine Learning (ML) approaches, especially LLMs , appear to be making great advances against long-standing Artificial Intelligence challenges. In particular, LLMs are increasingly achieving successes in areas both adjacent to, and overlapping with, those of interest to the Computational Models of Natural Argument community. A prevalent opinion, not without some basis, within the ML research community is that many, if not all, AI challenges, will eventually be solved by ML models of increasing power and utility, negating the need for alternative or traditional approaches. An exemplar of this position, is the study of distinct models of dialogue for inter-agent communication when LLM based chatbots are increasingly able to surpass their performance in specific contexts. The trajectory of increased LLM capabilities suggests no reason that this trend will not continue, at least for some time. However, it is not the case that only the one, or the other approach, is necessary. Despite a tendency for LLMs to feature creep, and to appear to subsume additional areas of study, there are very good reasons to consider three modes of study of dialogue. Firstly, LLMs as their own individual field within ML, secondly, dialogue both in terms of actual human behaviour, which can exhibit wide quality standards, but also in terms of normative and idealised models, and thirdly, the fertile area in which the two overlap and can operate collaboratively. It is this third aspect with which this paper is concerned, for the first will occur anyway as researchers seek to map out the boundaries of what LLMs, as AI models, can actually achieve, and the second will continue, because the study of how people interact naturally through argument and dialogue will remain both fascinating and of objective value regardless of advances made in LLMs. However, where LLMs, Dialogue Models, and, for completion, people, come together, there is fertile ground for the development of principled models of interaction that are well-founded, well-regulated, and supportive of mixed-initiative interactions between humans and intelligent software agents

Towards a declarative approach to constructing dialogue games.

In this paper we sketch a new approach to the development of dialogue games that builds upon the knowledge gained from several decades of dialogue game research across a variety of communities and which leverages the capabilities of the Dialogue Game Description Language as a means to describe the constituent parts of dialogue games. Our ultimate aim is to produce a method for rapidly describing and implementing games that conform to the designer's needs by declaring what is required and then automatically constructing the game from components, called 'fragments', that are distilled from existing dialogue games

Reconsidering RepStat rules in dialectic games.

Prohibition of repeated statements has benefits for the tractability and predictability of dialogues carried out by machines, but doesn't match the real world behaviour of people. This gap between human and machine behaviour leads to problems when formal dialectical systems are applied in conversational AI contexts. However, the problem of handling statement repetition gives insight into wider issues that stem partly from the historical focus on formal dialectics to the near exclusion of descriptive dialectics. In this paper we consider the problem of balancing the needs of machines versus those of human participants through the consideration of both descriptive and formal dialectics integrated within a single overarching dialectical system. We describe how this approach can be supported through minimal extension of the Dialogue Game Description Language

A comparison of cortical and trabecular bone from C57 Black 6 mice using Raman spectroscopy

Peer reviewedPostprin

S11RS SGB No. 5 (Finance Bylaws)

A BILL To amend Article VI, Section 8, Subsection C, of the Student Government By-Law

Science‐based interviewing: Information elicitation

This article describes an ethical and effective science‐based model of interviewing. An initial planning phase assists the investigative team in separating facts from inferences, decreases the likelihood of errors based on cognitive biases, and prompts careful preparation of the environment. The interview begins with an explanation of why the subject is being questioned. The interviewer then metaphorically hands the interview over to the subject, making him the talker and the interviewer the listener. The interviewer engages in active listening, soliciting as much information from the subject as possible by deploying tactics that enhance memory based on science, including elements of the cognitive interview. Cues to deception are found in the details of the story, rather than in signs of anxiety or nonverbal behaviours, and by deploying Strategic Use of Evidence. This model has been shown to increase cooperation, decrease resistance, and provoke useful information in real‐world criminal interviews

CLIC e+e- Linear Collider Studies

This document provides input from the CLIC e+e- linear collider studies to the update process of the European Strategy for Particle Physics. It is submitted on behalf of the CLIC/CTF3 collaboration and the CLIC physics and detector study. It describes the exploration of fundamental questions in particle physics at the energy frontier with a future TeV-scale e+e- linear collider based on the Compact Linear Collider (CLIC) two-beam acceleration technique. A high-luminosity high-energy e+e- collider allows for the exploration of Standard Model physics, such as precise measurements of the Higgs, top and gauge sectors, as well as for a multitude of searches for New Physics, either through direct discovery or indirectly, via high-precision observables. Given the current state of knowledge, following the observation of a \sim125 GeV Higgs-like particle at the LHC, and pending further LHC results at 8 TeV and 14 TeV, a linear e+e- collider built and operated in centre-of-mass energy stages from a few-hundred GeV up to a few TeV will be an ideal physics exploration tool, complementing the LHC. Two example scenarios are presented for a CLIC accelerator built in three main stages of 500 GeV, 1.4 (1.5) TeV, and 3 TeV, together with the layout and performance of the experiments and accompanied by cost estimates. The resulting CLIC physics potential and measurement precisions are illustrated through detector simulations under realistic beam conditions.Comment: Submitted to the European Strategy Preparatory Grou

The CLIC Programme: Towards a Staged e+e- Linear Collider Exploring the Terascale : CLIC Conceptual Design Report

This report describes the exploration of fundamental questions in particle physics at the energy frontier with a future TeV-scale e+e- linear collider based on the Compact Linear Collider (CLIC) two-beam acceleration technology. A high-luminosity high-energy e+e- collider allows for the exploration of Standard Model physics, such as precise measurements of the Higgs, top and gauge sectors, as well as for a multitude of searches for New Physics, either through direct discovery or indirectly, via high-precision observables. Given the current state of knowledge, following the observation of a 125 GeV Higgs-like particle at the LHC, and pending further LHC results at 8 TeV and 14 TeV, a linear e+e- collider built and operated in centre-of-mass energy stages from a few-hundred GeV up to a few TeV will be an ideal physics exploration tool, complementing the LHC. In this document, an overview of the physics potential of CLIC is given. Two example scenarios are presented for a CLIC accelerator built in three main stages of 500 GeV, 1.4 (1.5) TeV, and 3 TeV, together with operating schemes that will make full use of the machine capacity to explore the physics. The accelerator design, construction, and performance are presented, as well as the layout and performance of the experiments. The proposed staging example is accompanied by cost estimates of the accelerator and detectors and by estimates of operating parameters, such as power consumption. The resulting physics potential and measurement precisions are illustrated through detector simulations under realistic beam conditions.Comment: 84 pages, published as CERN Yellow Report https://cdsweb.cern.ch/record/147522

Identification of single-site gold catalysis in acetylene hydrochlorination

There remains considerable debate over the active form of gold under operating conditions of a recently validated gold catalyst for acetylene hydrochlorination. We have performed an in situ x-ray absorption fine structure study of gold/carbon (Au/C) catalysts under acetylene hydrochlorination reaction conditions and show that highly active catalysts comprise single-site cationic Au entities whose activity correlates with the ratio of Au(I):Au(III) present. We demonstrate that these Au/C catalysts are supported analogs of single-site homogeneous Au catalysts and propose a mechanism, supported by computational modeling, based on a redox couple of Au(I)-Au(III) species. View Full Tex

Effects of power variation on cycle performance during simulated hilly time-trials

It has previously been shown that cyclists are unable to maintain a constant power output during cycle time-trials on hilly courses. The purpose of the present study is therefore to quantify these effects of power variation using a mathematical model of cycling performance. A hypothetical cyclist (body mass: 70 kg, bicycle mass: 10 kg) was studied using a mathematical model of cycling, which included the effects of acceleration. Performance was modelled over three hypothetical 40-km courses, comprising repeated 2.5-km sections of uphill and downhill with gradients of 1%, 3%, and 6%, respectively. Amplitude (5–15%) and distance (0.31–20.00 km) of variation were modelled over a range of mean power outputs (200–600 W) and compared to sustaining a constant power. Power variation was typically detrimental to performance; these effects were augmented as the amplitude of variation and severity of gradient increased. Varying power every 1.25 km was most detrimental to performance; at a mean power of 200 W, performance was impaired by 43.90 s (±15% variation, 6% gradient). However at the steepest gradients, the effect of power variation was relatively independent of the distance of variation. In contrast, varying power in parallel with changes in gradient improved performance by 188.89 s (±15% variation, 6% gradient) at 200 W. The present data demonstrate that during hilly time-trials, power variation that does not occur in parallel with changes in gradient is detrimental to performance, especially at steeper gradients. These adverse effects are substantially larger than those previously observed during flat, windless time-trials