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Priming effects on labile and stable soil organic carbon decomposition: Pulse dynamics over two years.
Soil organic carbon (SOC) is a major component in the global carbon cycle. Yet how input of plant litter may influence the loss of SOC through a phenomenon called priming effect remains highly uncertain. Most published results about the priming effect came from short-term investigations for a few weeks or at the most for a few months in duration. The priming effect has not been studied at the annual time scale. In this study for 815 days, we investigated the priming effect of added maize leaves on SOC decomposition of two soil types and two treatments (bare fallow for 23 years, and adjacent old-field, represent stable and relatively labile SOC, respectively) of SOC stabilities within each soil type, using a natural 13C-isotope method. Results showed that the variation of the priming effect through time had three distinctive phases for all soils: (1) a strong negative priming phase during the first period (≈0-90 days); (2) a pulse of positive priming phase in the middle (≈70-160 and 140-350 days for soils from Hailun and Shenyang stations, respectively); and (3) a relatively stabilized phase of priming during the last stage of the incubation (>160 days and >350 days for soils from Hailun and Shenyang stations, respectively). Because of major differences in soil properties, the two soil types produced different cumulative priming effects at the end of the experiment, a positive priming effect of 3-7% for the Mollisol and a negative priming effect of 4-8% for the Alfisol. Although soil types and measurement times modulated most of the variability of the priming effect, relative SOC stabilities also influenced the priming effect for a particular soil type and at a particular dynamic phase. The stable SOC from the bare fallow treatment tended to produce a narrower variability during the first phase of negative priming and also during the second phase of positive priming. Averaged over the entire experiment, the stable SOC (i.e., the bare fallow) was at least as responsive to priming as the relatively labile SOC (i.e., the old-field) if not more responsive. The annual time scale of our experiment allowed us to demonstrate the three distinctive phases of the priming effect. Our results highlight the importance of studying the priming effect by investigating the temporal dynamics over longer time scales
EVF: An Extensible and Expressive Visitor Framework for Programming Language Reuse (Artifact)
This artifact is based on EVF, an extensible and expressive Java visitor framework. EVF aims at reducing the effort involved in creation and reuse of programming languages. EVF an annotation processor that automatically generate boilerplate ASTs and AST for a given an Object Algebra interface. This artifact contains source code of the case study on "Types and Programming Languages", illustrating how effective EVF is in modularizing programming languages. There is also a microbenchmark in the artifact that shows that EVF has reasonable performance with respect to traditional visitors
Multi-aspect Repetition Suppression and Content Moderation of Large Language Models
Natural language generation is one of the most impactful fields in NLP, and
recent years have witnessed its evolution brought about by large language
models (LLMs). As the key instrument for writing assistance applications, they
are generally prone to replicating or extending offensive content provided in
the input. In low-resource data regime, they can also lead to repetitive
outputs (Holtzman et al., 2019) [1]. Usually, offensive content and repetitions
are mitigated with post-hoc methods, including n-gram level blocklists, top-k
and nucleus sampling. In this paper, we introduce a combination of exact and
non-exact repetition suppression using token and sequence level unlikelihood
loss, repetition penalty during training, inference, and post-processing
respectively. We further explore multi-level unlikelihood loss to the extent
that it endows the model with abilities to avoid generating offensive words and
phrases from the beginning. Finally, with comprehensive experiments, we
demonstrate that our proposed methods work exceptionally in controlling the
repetition and content quality of LLM outputs
Compositional Programming (Artifact)
Our main paper presents CP, a Compositional Programming language in a statically typed modular programming style. This artifact includes its Haskell implementation, together with several examples and three case studies written in CP. All code snippets in our main paper can be type-checked and run using our CP interpreter
E2E-LOAD: End-to-End Long-form Online Action Detection
Recently, there has been a growing trend toward feature-based approaches for
Online Action Detection (OAD). However, these approaches have limitations due
to their fixed backbone design, which ignores the potential capability of a
trainable backbone. In this paper, we propose the first end-to-end OAD model,
termed E2E-LOAD, designed to address the major challenge of OAD, namely,
long-term understanding and efficient online reasoning. Specifically, our
proposed approach adopts an initial spatial model that is shared by all frames
and maintains a long sequence cache for inference at a low computational cost.
We also advocate an asymmetric spatial-temporal model for long-form and
short-form modeling effectively. Furthermore, we propose a novel and efficient
inference mechanism that accelerates heavy spatial-temporal exploration.
Extensive ablation studies and experiments demonstrate the effectiveness and
efficiency of our proposed method. Notably, we achieve 17.3 (+12.6) FPS for
end-to-end OAD with 72.4%~(+1.2%), 90.3%~(+0.7%), and 48.1%~(+26.0%) mAP on
THMOUS14, TVSeries, and HDD, respectively, which is 3x faster than previous
approaches. The source code will be made publicly available
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