Many manipulation tasks require memory beyond the current observation, yet most visuomotor policies rely on the Markov assumption and thus struggle with repeated states or long-horizon dependencies. Existing methods attempt to extend observation horizons but remain insufficient for diverse memory requirements. To this end, we propose an object-centric history representation based on point tracking, which abstracts past observations into a compact and structured form that retains only essential task-relevant information. Tracked points are encoded and aggregated at the object level, yielding a compact history representation that can be seamlessly integrated into various visuomotor policies. Our design provides full history-awareness with high computational efficiency, leading to improved overall task performance and decision accuracy. Through extensive evaluations on diverse manipulation tasks, we show that our method addresses multiple facets of memory requirements - such as task stage identification, spatial memorization, and action counting, as well as longer-term demands like continuous and pre-loaded memory - and consistently outperforms both Markovian baselines and prior history-based approaches. Project website: http://tonyfang.net/history
The first openly gay detective novel, one of the first overtly homosexual fictions published by a British press, and possibly the most popular fiction in the 1950s about male same-sex desire, The Heart in Exile (1953), was written under the pseudonym Rodney Garland. The author’s identity has sparked debates since the very first publication of the novel. Although it seems to be the common consensus that the novel was written by Hungarian journalist Adam de Hegedus, there are disputes about the person of the real author and the authorship of the Garland series. This paper first addresses these questions of authorship. Then, it moves on to argue that the novelty of The Heart in Exile in the early 1950s was the juxtaposition of glancing backward and forward, with emphasis on the novel’s treatment and uses of prior literary discourse.
Andrés Aceña, Bruno Cardin Guntsche, Ivan Gentile de Austria
We present a no-go theorem for spherically symmetric configurations of two charged fluid species in equilibrium. The fluid species are assumed to be dusts, that is, perfect fluids without pressure, and the equilibrium can be attained for a single dust from the balance of electrostatic repulsion and gravitational attraction. We show that this is impossible for two dust species unless both of them are indistinguishable in terms of their electric charge density to matter density ratio. The result is obtained in the main three theories of mechanics, that is, in Newtonian Mechanics, in Special Relativity and in General Relativity. In particular, as charged dust solutions have been used to study the possibility of black hole mimickers, this result shows that such mimickers can not be constructed unless the underlying charged particle has the correct charge to mass ratio.
Purpose The purpose of this paper is to reconstruct the marketing history of medical marijuana cigarettes in the past three decades of Austria-Hungary. Design/methodology/approach This paper constructs an analytical narrative based on information scattered in historical periodicals. Findings Towards the end of Habsburg rule, two Ljubljana-based pharmacists, the Trnkóczy brothers, managed to establish themselves as monopolistic suppliers of pre-rolled medical marijuana cigarettes for the entire Austrian part of the dual monarchy. Garnering the support of the regional Carniolan Government, Julius von Trnkóczy successfully argued his wares were not affected by the prohibition passed against imported French medicinal cigarettes. This happened despite medical opposition, suggesting that Trnkóczys could only operate this business because of their elevated social status. In the past decade of the 19th century, Ubald von Trnkóczy took advantage of newly loosened regulation to obtain an official permit by the royal-imperial government in Vienna. This was followed, in late 1909, by an advertising campaign covering mass media throughout the empire. This was enabled, amongst others, by a cutting down on medicinal claims. Their declining price is further indication that the cigarettes were mass marketed, especially as their core ingredient, cannabis, underwent price inflation. Research limitations/implications Because of its later illegality, the research subject was for a long time considered embarrassing, leading to an absence of retrievable documents. Missing archival sources are thus a major limitation, but one which can be overcome by the concurrent reading of historical periodicals – ranging from mass-market newspapers to specialist journals and legal texts. This paper has implications for 21st-century challenges in the marketing of newly legalized medical marijuana. Originality/value This paper discusses the marketing history of cannabis, a drug rarely discussed in historical literature outside its medical and regulatory context, and reconstructs previously forgotten case histories.
In many real-world games, such as traders repeatedly bargaining with customers, it is very hard for a single AI trader to make good deals with various customers in a few turns, since customers may adopt different strategies even the strategies they choose are quite simple. In this paper, we model this problem as fast adaptive learning in the finitely repeated games. We believe that past game history plays a vital role in such a learning procedure, and therefore we propose a novel framework (named, F3) to fuse the past and current game history with an Opponent Action Estimator (OAE) module that uses past game history to estimate the opponent's future behaviors. The experiments show that the agent trained by F3 can quickly defeat opponents who adopt unknown new strategies. The F3 trained agent obtains more rewards in a fixed number of turns than the agents that are trained by deep reinforcement learning. Further studies show that the OAE module in F3 contains meta-knowledge that can even be transferred across different games.
An effective email search engine can facilitate users' search tasks and improve their communication efficiency. Users could have varied preferences on various ranking signals of an email, such as relevance and recency based on their tasks at hand and even their jobs. Thus a uniform matching pattern is not optimal for all users. Instead, an effective email ranker should conduct personalized ranking by taking users' characteristics into account. Existing studies have explored user characteristics from various angles to make email search results personalized. However, little attention has been given to users' search history for characterizing users. Although users' historical behaviors have been shown to be beneficial as context in Web search, their effect in email search has not been studied and remains unknown. Given these observations, we propose to leverage user search history as query context to characterize users and build a context-aware ranking model for email search. In contrast to previous context-dependent ranking techniques that are based on raw texts, we use ranking features in the search history. This frees us from potential privacy leakage while giving a better generalization power to unseen users. Accordingly, we propose a context-dependent neural ranking model (CNRM) that encodes the ranking features in users' search history as query context and show that it can significantly outperform the baseline neural model without using the context. We also investigate the benefit of the query context vectors obtained from CNRM on the state-of-the-art learning-to-rank model LambdaMart by clustering the vectors and incorporating the cluster information. Experimental results show that significantly better results can be achieved on LambdaMart as well, indicating that the query clusters can characterize different users and effectively turn the ranking model personalized.
The spread of infectious disease in a human community or the proliferation of fake news on social media can be modeled as a randomly growing tree-shaped graph. The history of the random growth process is often unobserved but contains important information such as the source of the infection. We consider the problem of statistical inference on aspects of the latent history using only a single snapshot of the final tree. Our approach is to apply random labels to the observed unlabeled tree and analyze the resulting distribution of the growth process, conditional on the final outcome. We show that this conditional distribution is tractable under a shape-exchangeability condition, which we introduce here, and that this condition is satisfied for many popular models for randomly growing trees such as uniform attachment, linear preferential attachment and uniform attachment on a $D$-regular tree. For inference of the root under shape-exchangeability, we propose O(n log n) time algorithms for constructing confidence sets with valid frequentist coverage as well as bounds on the expected size of the confidence sets. We also provide efficient sampling algorithms that extend our methods to a wide class of inference problems.
A first insight into a new digital edition project of Arthur Schnitzler’s correspondence with eighty-six writers is the basis for a discussion of the methodological and epistemological transformations in editing in the last five decades. As a modernist writer, Schnitzler is one of the protagonists of the culture of letters. Bringing his correspondence into relation with his diary aims at not only reconstructing his “life” and “work”, but at visualizing transnational correspondence networks.
History of Austria. Liechtenstein. Hungary. Czechoslovakia
In this study Cristian surveys the life and work of Baroness Elemérné Bornemissza, née Karola Szilvássy (1876 – 1948), an internationalist Transylvanian aristocrat, primarily known as the famous literary patron of Erdélyi Helikon and lifelong muse of Count Miklós Bánffy de Losoncz, who immortalized her through the character of Adrienne Milóth in his Erdélyi trilógia [‘The Transylvanian Trilogy’]. Research on Karola Szilvássy is still scarce with little known about the life of this maverick woman, who did not comply with the norms of her society. She was an actress and film director during the silent film era, courageous nurse in the World War I, as well as unusual fashion trendsetter, gourmet cookbook writer, Africa traveler—in short, a source of inspiration for many women of her time, and after.
Edoardo Carlesi, Yehuda Hoffman, Stefan Gottlöber
et al.
In this work an ensemble of simulated Local Group analogues is used to constrain the properties of the mass assembly history of the Milky Way (MW) and Andromeda (M31) galaxies. These objects have been obtained using the constrained simulation technique, which ensures that simulated LGs live within a large scale environment akin to the observed one. Our results are compared against a standard $Λ$ Cold Dark Matter ($Λ$CDM) series of simulations which use the same cosmological parameters. This allows us to single out the effects of the constraints on the results. We find that (a) the median constrained merging histories for M31 and MW live above the standard ones at the 1-$σ$ level, (b) the median formation time takes place $\approx$ 0.5 Gyr earlier than unconstrained values, while the latest major merger happens on average 1.5 Gyr earlier and (c) the probability for both LG haloes to have experienced their last major merger in the first half of the history of the Universe is $\approx$ 50% higher for the constrained pairs. These results have been estimated to be significant at the 99% confidence level by means of a Kolmogorov-Simirnov test. These results suggest that the particular environment in which the Milky Way and Andromeda form plays a role in shaping their properties, and favours earlier formation and last major merger time values in agreement with other observational and theoretical considerations.
PurposeThe purpose of this paper is to illustrate how criminals launder money in the real estate business in Austria, Germany, Liechtenstein and Switzerland.Design/methodology/approachA qualitative content analysis of 58 semi-standardized expert interviews with both criminals and prevention experts and a quantitative survey of 184 compliance officers led to the identification of concrete techniques of money laundering in the real estate sector.FindingsReal estate companies in German-speaking countries in Europe continue to be extraordinarily suitable for money laundering. In particular, they can be used for placement, layering and integration, combined with violations of the tax code. Most importantly, however, they are the vehicles for one of the very few profitable methods of laundering money.Research limitations/implicationsAs the qualitative findings are based on semi-standardized interviews, these are limited to the 58 interviewees’ perspectives.Practical implicationsThe identification of gaps in existing anti-money laundering mechanisms is meant to provide compliance officers, law enforcement agencies and legislators with valuable insights into how criminals operate.Originality/valueWhile the existing literature focuses on organizations fighting money laundering and on the improvement of anti-money laundering measures, this paper describes how money launderers operate to avoid getting caught. Both prevention and criminal perspectives are taken into account.
Andrew Arrasmith, Lukasz Cincio, Andrew T. Sornborger
et al.
Although quantum computers are predicted to have many commercial applications, less attention has been given to their potential for resolving foundational issues in quantum mechanics. Here we focus on quantum computers' utility for the Consistent Histories formalism, which has previously been employed to study quantum cosmology, quantum paradoxes, and the quantum-to-classical transition. We present a variational hybrid quantum-classical algorithm for finding consistent histories, which should revitalize interest in this formalism by allowing classically impossible calculations to be performed. In our algorithm, the quantum computer evaluates the decoherence functional (with exponential speedup in both the number of qubits and the number of times in the history), and a classical optimizer adjusts the history parameters to improve consistency. We implement our algorithm on a cloud quantum computer to find consistent histories for a spin in a magnetic field, and on a simulator to observe the emergence of classicality for a chiral molecule.
Changing the name Margit Stellar (Mrs. József Krauss) to Anna, a pseudonym, Mrs. Sándor Dévényi, the real name of the writer whose journal is discussed in the article. Also, changing the name Szebenyi to Szebeny.
The original article can be found via the DOI: http://dx.doi.org/10.5195/ahea.2016.260
Szerb, Antal. 2017. Reflections in the Library: Selected Literary Essays 1926–1944 (ed. Zsuzsanna Varga, trans. Peter Sherwood). Cambridge, UK: Legenda. Studies in Comparative Literature 46. 132 pp.