Compositional Exemplars for In-context Learning

Large pretrained language models (LMs) have shown impressive In-Context Learning (ICL) ability, where the model learns to do an unseen task via a prompt consisting of input-output examples as the demonstration, without any parameter updates. The performance of ICL is highly dominated by the quality of the selected in-context examples. However, previous selection methods are mostly based on simple heuristics, leading to sub-optimal performance. In this work, we formulate in-context example selection as a subset selection problem. We propose CEIL (Compositional Exemplars for In-context Learning), which is instantiated by Determinantal Point Processes (DPPs) to model the interaction between the given input and in-context examples, and optimized through a carefully-designed contrastive learning objective to obtain preference from LMs. We validate CEIL on 12 classification and generation datasets from 7 distinct NLP tasks, including sentiment analysis, paraphrase detection, natural language inference, commonsense reasoning, open-domain question answering, code generation, and semantic parsing. Extensive experiments demonstrate not only the state-of-the-art performance but also the transferability and compositionality of CEIL, shedding new light on effective and efficient in-context learning. Our code is released at https://github.com/HKUNLP/icl-ceil.Comment: Accepted in ICML 202

A network SIS meta-population model with transportation flow

This paper considers a deterministic Susceptible-Infected-Susceptible (SIS) metapopulation model for the spread of a disease in a strongly connected network, where each node represents a large population. Individuals can travel between the nodes (populations). We derive a necessary and sufficient condition for the healthy equilibrium to be the unique equilibrium of the system, and then in fact it is asymptotically stable for all initial conditions (a sufficient condition for exponential stability is also given). If the condition is not satisfied, then there additionally exists a unique endemic equilibrium which is exponentially stable for all nonzero initial conditions. We then consider time-delay in the travel between nodes, and further investigate the role of the mobility rate that governs the flow of individuals between nodes in determining the convergence properties. We find that sometimes, increasing mobility helps the system converge to the healthy equilibrium.</p

AIGC Empowering Telecom Sector White Paper_chinese

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society

Polycyclopentene crystal-decorated carbon nanotubes by convenient large-scale in situ polymerization and their lotus leaf-like superhydrophobic films.

In situ Pd-catalyzed cyclopentene polymerization in the presence of multi-walled carbon nanotubes (MWCNTs) is demonstrated to effectively render, on a large scale, polycyclopentene-crystal-decorated MWCNTs. Controlling the catalyst loading and/or time in the polymerization offers a convenient tuning of the polymer content and the morphology of the decorated MWCNTs. Appealingly, films made of the decorated carbon nanotubes through simple vacuum filtration show the characteristic lotus-leaf-like superhydrophobicity with high water contact angle (>150°), low contact angle hysteresis (<10°), and low water adhesion, while being electrically conductive. This is the first demonstration of the direct fabrication of lotus-leaf-like superhydrophobic films with solution-grown polymer-crystal-decorated carbon nanotube

ATP6L promotes metastasis of colorectal cancer by inducing epithelial-mesenchymal transition

ATP6L, the C subunit of the V-ATPase V0 domain, is involved in regulating the acidic tumor micro-environment and may promote tumor progression. However, the expression and functional role of ATP6L in tumors have not yet been well explored. In this study, we found that ATP6L protein overexpression was related to colorectal cancer histological differentiation (P <0.001), presence of metastasis (P <0.001) and recurrence (P = 0.02). ATP6L expression in the liver metastatic foci was higher than in the primary foci (P = 0.04). ATP6L expression was notably concomitant with epithelial-mesenchymal transition (EMT) immunohistochemical features, such as reduced expression of the epithelial marker E-cadherin (P = 0.021) and increased expression of the mesenchymal marker vimentin (P = 0.004). Results of in vitro and in vivo experiments showed that ATP6L expression could alter cell morphology, regulate EMT-associated protein expression, and enhance migration and invasion. The effect of ATP6L on metastasis was further demonstrated in a tail vein injection mice model. In addition, the mouse xenograft model showed that ATP6L-overexpressing HCT116 cells grew into larger tumor masses, showed less necrosis and formed more micro-vessels than the control cells. Taken together, our results suggest that ATP6L promotes metastasis of colorectal cancer by inducing EMT and angiogenesis, and is a potential target for tumor therapy

Ultra-small carbon nanospheres (< 50 nm) of uniform tunable sizes by a convenient catalytic emulsion polymerization strategy: superior supercapacitive and sorption performances

Porous carbon nanospheres have received enormous attention for various applications. Though there are several elegant strategies existing for the synthesis of relatively large carbon nanospheres (> ca. 100 nm), the synthesis of carbon nanospheres with well-defined tunable ultra-small sizes (< 50 nm) has often been challenging while such ultra-small nanospheres are much more valuable. A novel, convenient, and scalable catalytic emulsion polymerization technique is demonstrated in this paper for highly efficient synthesis of ultra-small carbon nanospheres with uniform tunable sizes in the range of 11–38 nm. In this strategy, a simple change of the emulsion polymerization recipe renders a convenient yet efficient tuning of the size of the carbon nanospheres. In particular, activated carbon nanospheres (A-CNS21 of average size of 21 nm) obtained by carbonization in the presence of KOH as the chemical activation agent is featured with very high surface area (2,360 m2/g) and the desired hierarchical macro-/meso-/micropore structures resulting from nanosphere packing/aggregation. A-CNS21 is demonstrated to have superior high-rate supercapacitive performances and outstanding sorption capacities towards volatile organic compounds (VOCs), H2, and CO2, which are comparable to or even better than the best results reported to date in these applications. To the best of our knowledge, this is the first synthesis of ultrasmall carbon nanospheres with uniform tunable sizes and superior performances for these applications by the emulsion polymerization strategy