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Found 23 papers, 8 papers with code
Error Classification of Large Language Models on Math Word Problems: A Dynamically Adaptive Framework
To reduce human bias and enable fine-grained analysis of error patterns, we propose a novel framework for automated dynamic error classification in mathematical reasoning.
Machine Learning Analysis of Anomalous Diffusion
The rapid advancements in machine learning have made its application to anomalous diffusion analysis both essential and inevitable.
Explainable LLM-driven Multi-dimensional Distillation for E-Commerce Relevance Learning
Effective query-item relevance modeling is pivotal for enhancing user experience and safeguarding user satisfaction in e-commerce search systems.
Think Before You Act: A Two-Stage Framework for Mitigating Gender Bias Towards Vision-Language Tasks
During answer inference, GAMA integrates the image, generated narrative, and a task-specific question prompt to infer answers for different vision-language tasks.
A Novel Wide-Area Multiobject Detection System with High-Probability Region Searching
To address these challenges, this paper presents a hybrid system that incorporates a wide-angle camera, a high-speed search camera, and a galvano-mirror.
InternLM2 Technical Report
The evolution of Large Language Models (LLMs) like ChatGPT and GPT-4 has sparked discussions on the advent of Artificial General Intelligence (AGI).
Ranked #5 on
Long-Context Understanding
on Ada-LEval (BestAnswer)
Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem
This paper presents a new method for evaluating LLM hallucination in Question Answering (QA) based on the unanswerable math word problem (MWP).
Weakly Supervised Segmentation of Vertebral Bodies with Iterative Slice-propagation
In this paper, we propose a Weakly supervised Iterative Spinal Segmentation (WISS) method leveraging only four corner landmark weak labels on a single sagittal slice to achieve automatic volumetric segmentation from CT images for VBs.
Learning-based Bone Quality Classification Method for Spinal Metastasis
In this paper, we explore a learning-based automatic bone quality classification method for spinal metastasis based on CT images.
Memory efficient location recommendation through proximity-aware representation
Sequential location recommendation plays a huge role in modern life, which can enhance user experience, bring more profit to businesses and assist in government administration.
Cognition-Mode Aware Variational Representation Learning Framework for Knowledge Tracing
The Knowledge Tracing (KT) task plays a crucial role in personalized learning, and its purpose is to predict student responses based on their historical practice behavior sequence.
No Length Left Behind: Enhancing Knowledge Tracing for Modeling Sequences of Excessive or Insufficient Lengths
Knowledge tracing (KT) aims to predict students' responses to practices based on their historical question-answering behaviors.
Counterfactual Monotonic Knowledge Tracing for Assessing Students' Dynamic Mastery of Knowledge Concepts
Since students' mastery of knowledge concepts is often unlabeled, existing KT methods rely on the implicit paradigm of historical practice to mastery of knowledge concepts to students' responses to practices to address the challenge of unlabeled concept mastery.
Multi-source Education Knowledge Graph Construction and Fusion for College Curricula
The field of education has undergone a significant transformation due to the rapid advancements in Artificial Intelligence (AI).
PCRED: Zero-shot Relation Triplet Extraction with Potential Candidate Relation Selection and Entity Boundary Detection
To address the above issues, we propose a novel method named PCRED for ZeroRTE with Potential Candidate Relation Selection and Entity Boundary Detection.
WSC-Trans: A 3D network model for automatic multi-structural segmentation of temporal bone CT
Cochlear implantation is currently the most effective treatment for patients with severe deafness, but mastering cochlear implantation is extremely challenging because the temporal bone has extremely complex and small three-dimensional anatomical structures, and it is important to avoid damaging the corresponding structures when performing surgery.
Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction
Moreover, to estimate CVR upon the freshly observed but biased distribution with fake negatives, the importance sampling is widely used to reduce the distribution bias.
The two-dimensional OLCT of angularly periodic functions in polar coordinates
The two-dimensional (2D) offset linear canonical transform (OLCT) in polar coordinates plays an important role in many fields of optics and signal processing.
Unlimited Sampling Theorem Based on Fractional Fourier Transform
The recovery of bandlimited signals with high dynamic range is a hot issue in sampling research.
Towards a Better Tradeoff between Effectiveness and Efficiency in Pre-Ranking: A Learnable Feature Selection based Approach
In real-world search, recommendation, and advertising systems, the multi-stage ranking architecture is commonly adopted.
Wireless Coded Caching Can Overcome the Worst-User Bottleneck by Exploiting Finite File Sizes
We address the worst-user bottleneck of wireless coded caching, which is known to severely diminish cache-aided multicasting gains due to the fundamental worst-channel limitation of multicasting transmission.
Information Theory Information Theory
Study on Transient Spectrum Based on Charge Transfer of Semiconductor Quantum Dots
With the increasing energy crisis and the concept of green sustainable development, quantum dot materials have become a hot spot in the academic and industrial fields of chemistry because of their unique characteristics.
Mesoscale and Nanoscale Physics Strongly Correlated Electrons Instrumentation and Detectors Quantum Physics
Diagnostics for Variational Bayes approximations
Variational Bayes (VB) has shown itself to be a powerful approximation method in many application areas.
Computation
