131 research outputs found
CoTDet: Affordance Knowledge Prompting for Task Driven Object Detection
Task driven object detection aims to detect object instances suitable for
affording a task in an image. Its challenge lies in object categories available
for the task being too diverse to be limited to a closed set of object
vocabulary for traditional object detection. Simply mapping categories and
visual features of common objects to the task cannot address the challenge. In
this paper, we propose to explore fundamental affordances rather than object
categories, i.e., common attributes that enable different objects to accomplish
the same task. Moreover, we propose a novel multi-level chain-of-thought
prompting (MLCoT) to extract the affordance knowledge from large language
models, which contains multi-level reasoning steps from task to object examples
to essential visual attributes with rationales. Furthermore, to fully exploit
knowledge to benefit object recognition and localization, we propose a
knowledge-conditional detection framework, namely CoTDet. It conditions the
detector from the knowledge to generate object queries and regress boxes.
Experimental results demonstrate that our CoTDet outperforms state-of-the-art
methods consistently and significantly (+15.6 box AP and +14.8 mask AP) and can
generate rationales for why objects are detected to afford the task.Comment: Accepted by ICCV 202
Contrastive Grouping with Transformer for Referring Image Segmentation
Referring image segmentation aims to segment the target referent in an image
conditioning on a natural language expression. Existing one-stage methods
employ per-pixel classification frameworks, which attempt straightforwardly to
align vision and language at the pixel level, thus failing to capture critical
object-level information. In this paper, we propose a mask classification
framework, Contrastive Grouping with Transformer network (CGFormer), which
explicitly captures object-level information via token-based querying and
grouping strategy. Specifically, CGFormer first introduces learnable query
tokens to represent objects and then alternately queries linguistic features
and groups visual features into the query tokens for object-aware cross-modal
reasoning. In addition, CGFormer achieves cross-level interaction by jointly
updating the query tokens and decoding masks in every two consecutive layers.
Finally, CGFormer cooperates contrastive learning to the grouping strategy to
identify the token and its mask corresponding to the referent. Experimental
results demonstrate that CGFormer outperforms state-of-the-art methods in both
segmentation and generalization settings consistently and significantly.Comment: Accepted by CVPR 202
DDCoT: Duty-Distinct Chain-of-Thought Prompting for Multimodal Reasoning in Language Models
A long-standing goal of AI systems is to perform complex multimodal reasoning
like humans. Recently, large language models (LLMs) have made remarkable
strides in such multi-step reasoning on the language modality solely by
leveraging the chain of thought (CoT) to mimic human thinking. However, the
transfer of these advancements to multimodal contexts introduces heightened
challenges, including but not limited to the impractical need for
labor-intensive annotation and the limitations in terms of flexibility,
generalizability, and explainability. To evoke CoT reasoning in multimodality,
this work first conducts an in-depth analysis of these challenges posed by
multimodality and presents two key insights: "keeping critical thinking" and
"letting everyone do their jobs" in multimodal CoT reasoning. Furthermore, this
study proposes a novel DDCoT prompting that maintains a critical attitude
through negative-space prompting and incorporates multimodality into reasoning
by first dividing the reasoning responsibility of LLMs into reasoning and
recognition and then integrating the visual recognition capability of visual
models into the joint reasoning process. The rationales generated by DDCoT not
only improve the reasoning abilities of both large and small language models in
zero-shot prompting and fine-tuning learning, significantly outperforming
state-of-the-art methods but also exhibit impressive generalizability and
explainability.Comment: 24 pages, 13 figures, to be published in NeurIPS 202
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Negative Mood State Enhances the Susceptibility to Unpleasant Events: Neural Correlates from a Music-Primed Emotion Classification Task
Background: Various affective disorders are linked with enhanced processing of unpleasant stimuli. However, this link is likely a result of the dominant negative mood derived from the disorder, rather than a result of the disorder itself. Additionally, little is currently known about the influence of mood on the susceptibility to emotional events in healthy populations.Method: Event-Related Potentials (ERP) were recorded for pleasant, neutral and unpleasant pictures while subjects performed an emotional/neutral picture classification task during positive, neutral, or negative mood induced by instrumental Chinese music.Results: Late Positive Potential (LPP) amplitudes were positively related to the affective arousal of pictures. The emotional responding to unpleasant pictures, indicated by the unpleasant-neutral differences in LPPs, was enhanced during negative compared to neutral and positive moods in the entire LPP time window (600–1000 ms). The magnitude of this enhancement was larger with increasing self-reported negative mood. In contrast, this responding was reduced during positive compared to neutral mood in the 800–1000 ms interval. Additionally, LPP reactions to pleasant stimuli were similar across positive, neutral and negative moods except those in the 800–900 ms interval.Implications: Negative mood intensifies the humans' susceptibility to unpleasant events in healthy individuals. In contrast, music-induced happy mood is effective in reducing the susceptibility to these events. Practical implications of these findings were discussed.</p
The association between social media use and well-being during quarantine period: testing a moderated mediation model
ObjectivesSocial media use (SMU) increased dramatically during COVID-19 due to policies such as long-term quarantine. Given that SMU has complex effects on individuals’ well-being, this study aimed to explore the relationship between SMU and subjective well-being and the influencing factors in the context of the pandemic in China.MethodsA total of 895 adults (413 males) in different risk areas across China participated in this study. They provided self-reported data on subjective well-being, social media use, adaptive humor, and other demographic variables.ResultsIt revealed that SMU was positively associated with individual well-being, an effect partially mediated by the score of adaptive humor. Furthermore, the effect of SMU on adaptive humor was moderated by trait optimism, with the effect more robust in high (vs. low) optimistic individuals.ConclusionThis study explored the positive effects of SMU on individuals’ well-being, suggesting that individuals may better cope with negative experiences and maintain well-being under quarantine by showing more adaptive humor on social media
Cavity-enhanced and spatial-multimode spin-wave-photon quantum interface
Practical realizations of quantum repeaters require quantum memory
simultaneously providing high retrieval efficiency, long lifetime and multimode
storages. So far, the combination of high retrieval efficiency and spatially
multiplexed storages into a single memory remains challenging. Here, we set up
a ring cavity that supports an array including 6 TEM00 modes and then
demonstrated cavity enhanced and spatially multiplexed spin wave photon quantum
interface (QI). The cavity arrangement is according to Fermat' optical theorem,
which enables the six modes to experience the same optical length per round
trip. Each mode includesn horizontal and vertical polarizations. Via DLCZ
process in a cold atomic ensemble, we create non classically correlated pairs
of spin waves and Stokes photons in the 12 modes. The retrieved fields from the
multiplexed SWs are enhanced by the cavity and the average intrinsic retrieval
efficiency reaches 70% at zero delay. The storage time for the case that
cross-correlation function of the multiplexed QI is beyond 2 reaches 0.6ms
Systematic Fusion of Multi-Source Cognitive Networks With Graph Learning - A Study on Fronto-Parietal Network
Cognitive tasks induce fluctuations in the functional connectivity between brain regions which constitute cognitive networks in the human brain. Although several cognitive networks have been identified, consensus still cannot be achieved on the precise borders and distribution of involved brain regions for each network, due to the multifarious use of diverse brain atlases in different studies. To address the problem, the current study proposed a novel approach to generate a fused cognitive network with the optimal performance in discriminating cognitive states by using graph learning, following the synthesization of one cognitive network defined by different brain atlases, and the construction of a hierarchical framework comprised of one main version and other supplementary versions of the specific cognitive network. As a result, the proposed method demonstrated better results compared with other machine learning methods for recognizing cognitive states, which was revealed by analyzing an fMRI dataset related to the mental arithmetic task. Our findings suggest that the fused cognitive network provides the potential to develop new mind decoding approaches
Histone modification signature at myeloperoxidase and proteinase 3 in patients with anti-neutrophil cytoplasmic autoantibody-associated vasculitis
Abstract Background Anti-neutrophil cytoplasmic autoantibody (ANCA)-associated vasculitis (AAV) is a systemic autoimmune disease characterized by destructive vascular inflammation. Two prominent ANCA autoantigens are myeloperoxidase (MPO) and proteinase 3 (PR3), and transcription of MPO and PRTN3, the genes encoding the autoantigens, is associated with disease activity. We investigated whether patients with AAV have alterations in histone modifications, particularly those associated with transcriptional activation, at MPO and PRTN3. Results We identified a network of genes regulating histone modifications that were differentially expressed in AAV patients compared to healthy controls. We focused on four genes (EHMT1 and EHMT2, ING4, and MSL1) and found their expression correlated with expression of MPO and PRTN3. Methylation of histone H3K9, catalyzed by EHMT1 and EHMT2 and associated with gene silencing, was most depleted at MPO and PRTN3 in patients with active disease and the highest MPO and PRTN3 expression. Acetylation of histone H4K16, modified by complexes containing ING4 and MSL1 and associated with gene activation, was most enriched at MPO and PRTN3 in patients with active disease and the highest MPO and PRTN3 expression. Methylation at H3K4, a mark of transcriptional activation, was enriched at MPO and PRTN3 in patients and healthy controls. Conclusions MPO and PRTN3 in neutrophils of AAV patients with active disease have a distinct pattern of histone modifications, which implicates epigenetic mechanisms in regulating expression of autoantigen genes and suggests that the epigenome may be involved in AAV pathogenesis
ANCA patients have T cells responsive to complementary PR-3 antigen
Some patients with proteinase 3 specific anti-neutrophil cytoplasmic autoantibodies (PR3-ANCA) also have antibodies that react to complementary-PR3 (cPR3), a protein encoded by the antisense RNA of the PR3 gene. To study whether patients with anti-cPR3 antibodies have cPR3-responsive memory T cells we selected conditions that allowed cultivation of memory cells but not naïve cells. About half of the patients were found to have CD4+TH1 memory cells responsive to the cPR3138-169-peptide; while only a third of the patients had HI-PR3 protein responsive T cells. A significant number of T cells from patients responded to cPR3138-169 peptide and to HI-PR3 protein by proliferation and/or secretion of IFN-γ, compared to healthy controls while there was no response to scrambled peptide. Cells responsive to cPR3138-169-peptide were not detected in MPO-ANCA patients suggesting that this response is specific. The HLADRB1* 15 allele was significantly overrepresented in our patient group and is predicted to bind cPR3138-169 peptide with high affinity. Regression analysis showed a significant likelihood that anti-cPR3 antibodies and cPR3-specific T cells coexist in individuals, consistent with an immunological history of encounter with a PR3-complementary protein. We suggest that the presence of cells reacting to potential complementary protein pairs might provide an alternative mechanism for auto-immune diseases
The regulation of induced depression during a frustrating situation: benefits of expressive suppression in Chinese individuals.
BACKGROUND: Studies from European-American cultures consistently reported that expressive suppression was associated with worse emotional consequence (e.g. depression) in comparison with acceptance. However, this conclusion may not apply to Chinese, as suppressing emotional displays to maintain relational harmony is culturally valued in East Asian countries. Thus, the present study examined the effects of suppression and acceptance on the depressive mood induced by a frustrating task in a Chinese sample. METHOD: Sixty-four subjects were randomly assigned to one of three instructions: suppression, acceptance or no-regulation during a frustrating arithmetic task. The experience of depressive emotion and skin conductance response (SCR) were recorded during pre-frustration baseline, frustration induction and post-frustration recovery phases, respectively. RESULTS: Compared with the control and acceptance instructions, suppression instruction was associated with decreased depressive experiences and smaller SCR activity during frustration. There were no significant differences between acceptance and control groups in both subjective depression and SCR activity during frustration. Moreover, the suppression group showed a better emotional recovery after the frustrating task, in comparison with the acceptance and control groups. Correlation analyses verified that SCR reactivity was a reliable index of experienced depression during the frustration. CONCLUSIONS: Expressive suppression is effective in reducing depressive experiences and depression-related physiological activity (SCR) when Chinese people are involved. By contrast, the acceptance of depressive emotion in Chinese people does not produce a similar regulation effect. These findings suggest that cultural context should be considered in understanding the emotional consequences of suppression and acceptance strategies
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