Approximating Word Ranking and Negative Sampling for Word Embedding

CBOW (Continuous Bag-Of-Words) is one of the most commonly used techniques to generate word embeddings in various NLP tasks. However, it fails to reach the optimal performance due to uniform involvements of positive words and a simple sampling distribution of negative words. To resolve these issues, we propose OptRank to optimize word ranking and approximate negative sampling for bettering word embedding. Specifically, we first formalize word embedding as a ranking problem. Then, we weigh the positive words by their ranks such that highly ranked words have more importance, and adopt a dynamic sampling strategy to select informative negative words. In addition, an approximation method is designed to efficiently compute word ranks. Empirical experiments show that OptRank consistently outperforms its counterparts on a benchmark dataset with different sampling scales, especially when the sampled subset is small. The code and datasets can be obtained from https://github.com/ouououououou/OptRank

Unexpected Hydrated Electron Source for Preparative Visible-Light Driven Photoredox Catalysis

The hydrated electron is experiencing a renaissance as a superreductant in lab-scale reductions driven by light, both for the degradation of recalcitrant pollutants and for challenging chemical reactions. However, examples for its sustainable generation under mild conditions are scarce. By combining a water-soluble Ir catalyst with unique photochemical properties and an inexpensive diode laser as light source, we produce hydrated electrons through a two-photon mechanism previously thought to be unimportant for laboratory applications. Adding cheap sacrificial donors turns our new hydrated electron source into a catalytic cycle operating in pure water over a wide pH range. Not only is that catalytic system capable of detoxifying a chlorinated model compound with turnover numbers of up to 200, but it can also be employed for two novel hydrated electron reactions, namely, the decomposition of quaternary ammonium compounds and the conversion of trifluoromethyl to difluoromethyl groups

Electron Accumulation on Naphthalene Diimide Photosensitized by [Ru(2,2′-Bipyridine)3]2+

In a molecular triad comprised of a central naphthalene diimide (NDI) unit flanked by two [Ru(bpy)3]2+ (bpy = 2,2′-bipyridine) sensitizers, NDI2– is formed after irradiation with visible light in deaerated CH3CN in the presence of excess triethylamine. The mechanism for this electron accumulation involves a combination of photoinduced and thermal elementary steps. In a structurally related molecular pentad with two peripheral triarylamine (TAA) electron donors attached covalently to a central [Ru(bpy)3]2+-NDI-[Ru(bpy)3]2+ core but no sacrificial reagents present, photoexcitation only leads to NDI– (and TAA+), whereas NDI2– is unattainable due to rapid electron transfer events counteracting charge accumulation. For solar energy conversion, this finding means that fully integrated systems with covalently linked photosensitizers and catalysts are not necessarily superior to multicomponent systems, because the fully integrated systems can suffer from rapid undesired electron transfer events that impede multielectron reactions on the catalyst

Electron Transfer across o-Phenylene Wires

Photoinduced electron transfer across rigid rod-like oligo-p-phenylenes has been thoroughly investigated in the past, but their o-connected counterparts are yet entirely unexplored in this regard. We report on three molecular dyads comprised of a triarylamine donor and a Ru(bpy)32+ (bpy =2,2′-bipyridine) acceptor connected covalently by 2 to 6 o-phenylene units. Pulsed excitation of the Ru(II) sensitizer at 532 nm leads to the rapid formation of oxidized triarylamine and reduced ruthenium complex via intramolecular electron transfer. The subsequent thermal reverse charge-shift reaction to reinstate the electronic ground-state occurs on a time scale of 120–220 ns in deaerated CH3CN at 25 °C. The conformational flexibility of the o-phenylene bridges causes multiexponential transient absorption kinetics for the photoinduced forward process, but the thermal reverse reaction produces single-exponential transient absorption decays. The key finding is that the flexible o-phenylene bridges permit rapid formation of photoproducts storing ca. 1.7 eV of energy with lifetimes on the order of hundreds of nanoseconds, similar to what is possible with rigid rod-like donor–acceptor compounds. Thus, the conformational flexibility of the o-phenylenes represents no disadvantage with regard to the photoproduct lifetimes, and this is relevant in the greater context of light-to-chemical energy conversion

A Molybdenum(0) Isocyanide Analogue of [Ru(2,2'-Bipyridine)3]2+: Strong Reductant for Photoredox Catalysis

We report the first homoleptic Mo0 complex with bidentate isocyanide ligands, which exhibits metal-to-ligand charge transfer (3MLCT) luminescence with quantum yields and lifetimes similar to Ru(bpy)32+ (bpy=2,2′-bipyridine). This Mo0 complex is a very strong photoreductant, which manifests in its capability to reduce acetophenone with essentially diffusion-limited kinetics as shown by time-resolved laser spectroscopy. The application potential of this complex for photoredox catalysis was demonstrated by the rearrangement of an acyl cyclopropane to a 2,3-dihydrofuran, which is a reaction that requires a reduction potential so negative that even the well-known and strongly reducing Ir(2-phenylpyridine)3 photosensitizer cannot catalyze it. Our study thus provides the proof-of-concept for the use of chelating isocyanides to obtain Mo0 complexes with long-lived 3MLCT excited states that are applicable to unusually challenging photoredox chemistry

VSE-ens: Visual-Semantic Embeddings with Efficient Negative Sampling

Jointing visual-semantic embeddings (VSE) have become a research hotpot for the task of image annotation, which suffers from the issue of semantic gap, i.e., the gap between images' visual features (low-level) and labels' semantic features (high-level). This issue will be even more challenging if visual features cannot be retrieved from images, that is, when images are only denoted by numerical IDs as given in some real datasets. The typical way of existing VSE methods is to perform a uniform sampling method for negative examples that violate the ranking order against positive examples, which requires a time-consuming search in the whole label space. In this paper, we propose a fast adaptive negative sampler that can work well in the settings of no figure pixels available. Our sampling strategy is to choose the negative examples that are most likely to meet the requirements of violation according to the latent factors of images. In this way, our approach can linearly scale up to large datasets. The experiments demonstrate that our approach converges 5.02x faster than the state-of-the-art approaches on OpenImages, 2.5x on IAPR-TCI2 and 2.06x on NUS-WIDE datasets, as well as better ranking accuracy across datasets.Comment: Published by The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18