We study the multi-round response generation in visual dialog, where a response is generated according to a visually grounded conversational history. Given a triplet: an image, Q&A history, and current question, all the prevailing methods follow a codec (i.e., encoder-decoder) fashion in a supervised learning paradigm: a multimodal encoder encodes the triplet into a feature vector, which is then fed into the decoder for the current answer generation, supervised by the ground-truth. However, this conventional supervised learning does NOT take into account the impact of imperfect history, violating the conversational nature of visual dialog and thus making the codec more inclined to learn history bias but not contextual reasoning. To this end, inspired by the actor-critic policy gradient in reinforcement learning, we propose a novel training paradigm called History-Advantage Sequence Training (HAST). Specifically, we intentionally impose wrong answers in the history, obtaining an adverse critic, and see how the historic error impacts the codec's future behavior by History Advantagea quantity obtained by subtracting the adverse critic from the gold reward of ground-truth history. Moreover, to make the codec more sensitive to the history, we propose a novel attention network called History-Aware Co-Attention Network (HACAN) which can be effectively trained by using HAST. Experimental results on three benchmarks: VisDial v0.9&v1.0 and GuessWhat?!, show that the proposed HAST strategy consistently outperforms the state-of-the-art supervised counterparts.

Singlet oxygen ( 1 O 2 ) plays a pivotal role in numerous catalytic oxidation processes utilized in water purification and chemical synthesis. The spin-trapping method based on electron paramagnetic resonance (EPR) analysis is commonly employed for 1 O 2 detection. However, it is often limited to time-independent acquisition. Recent studies have raised questions about the reliability of the 1 O 2 trapper, 2,2,6,6-tetramethylpiperidine (TEMP), in various systems. In this study, we introduce a comprehensive, kinetic examination to monitor the spin-trapping process in EPR analysis. The EPR intensity of the trapping product was used as a quantitative measurement to evaluate the concentration of 1 O 2 in aqueous systems. This in situ kinetic study was successfully applied to a classical photocatalytic system with exceptional accuracy. Furthermore, we demonstrated the feasibility of our approach in more intricate 1 O 2 -driven catalytic oxidation processes for water decontamination and elucidated the molecular mechanism of direct TEMP oxidation. This method can avoid the false-positive results associated with the conventional 2D 1 O 2 detection techniques, and provide insights into the reaction mechanisms in 1 O 2 -dominated catalytic oxidation processes. This work underscores the necessity of kinetic studies for spin-trapping EPR analysis, presenting an avenue for a comprehensive exploration of the mechanisms governing catalytic oxidation processes.

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