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Found 19 papers, 8 papers with code
SpecNFS: A Challenge Dataset Towards Extracting Formal Models from Natural Language Specifications
Evaluations show that even when using a state-of-the-art language model, there is significant room for improvement, with the best models achieving an F1 score of only 60. 5 and 33. 3 in the named-entity-recognition and dependency-link-prediction sub-tasks, respectively.
ReFF: Reinforcing Format Faithfulness in Language Models across Varied Tasks
Without any annotated data, ReFF can substantially improve the format faithfulness rate (e. g., from 21. 6% in original LLaMA3 to 95. 0% on caption segmentation task), while keep the general quality comparable (e. g., from 47. 3 to 46. 4 in F1 scores).
High-Resolution Cloud Detection Network
The complexity of clouds, particularly in terms of texture detail at high resolutions, has not been well explored by most existing cloud detection networks.
GVDIFF: Grounded Text-to-Video Generation with Diffusion Models
In text-to-video (T2V) generation, significant attention has been directed toward its development, yet unifying discrete and continuous grounding conditions in T2V generation remains under-explored.
ScanFormer: Referring Expression Comprehension by Iteratively Scanning
This inspires us to explore a question: can we eliminate linguistic-irrelevant redundant visual regions to improve the efficiency of the model?
A New Approach to Intuitionistic Fuzzy Decision Making Based on Projection Technology and Cosine Similarity Measure
The objective of the presented pa-per is to develop a MADM method and medical diagnosis method under IFS using the projection technology and cosine similarity measure.
MetaGait: Learning to Learn an Omni Sample Adaptive Representation for Gait Recognition
Towards this goal, MetaGait injects meta-knowledge, which could guide the model to perceive sample-specific properties, into the calibration network of the attention mechanism to improve the adaptiveness from the omni-scale, omni-dimension, and omni-process perspectives.
GaitGCI: Generative Counterfactual Intervention for Gait Recognition
Gait is one of the most promising biometrics that aims to identify pedestrians from their walking patterns.
Referring Expression Comprehension Using Language Adaptive Inference
Different from universal object detection, referring expression comprehension (REC) aims to locate specific objects referred to by natural language expressions.
Language Adaptive Weight Generation for Multi-task Visual Grounding
The active perception can take expressions as priors to extract relevant visual features, which can effectively alleviate the mismatches.
Evolutionary Games on Networks: Phase Transition, Quasi-equilibrium, and Mathematical Principles
The stable cooperation ratio of spatial evolutionary games has been widely studied using simulations or approximate analysis methods.
Attentive Q-Matrix Learning for Knowledge Tracing
This is the main idea of Knowledge Tracing (KT), which models students' mastery of knowledge concepts (KCs, skills needed to solve a question) based on their past interactions on platforms.
An Entropy-based Measure of Intelligence Degree of System Structures
A measure of intelligence degree is proposed, with which the intelligence degree of several basic structures is calculated.
Deep transfer learning method based on automatic domain alignment and moment matching
Therefore, in this paper, a deep transfer learning method based on automatic domain alignment and moment matching (DA-MM) is proposed.
Self-paced Multi-grained Cross-modal Interaction Modeling for Referring Expression Comprehension
As an important and challenging problem in vision-language tasks, referring expression comprehension (REC) generally requires a large amount of multi-grained information of visual and linguistic modalities to realize accurate reasoning.
The Open Brands Dataset: Unified brand detection and recognition at scale
To the best of our knowledge, it is the largest dataset for brand detection and recognition with rich annotations.
Balanced joint maximum mean discrepancy for deep transfer learning
B-JMMD achieves the effect of balanced distribution adaptation for deep network architecture, and can be treated as an improved version of JMMD’s backpropagation algorithm.
Type-II 2HDM under the Precision Measurements at the $Z$-pole and a Higgs Factory
We also find that the expected accuracies at the $Z$-pole and at a Higgs factory are quite complementary in constraining mass splittings of heavy Higgs bosons.
High Energy Physics - Phenomenology
Modulation Classification via Gibbs Sampling Based on a Latent Dirichlet Bayesian Network
A novel Bayesian modulation classification scheme is proposed for a single-antenna system over frequency-selective fading channels.
