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Found 9 papers, 6 papers with code
Collaborative Cognitive Diagnosis with Disentangled Representation Learning for Learner Modeling
Motivated by the success of collaborative modeling in various domains, such as recommender systems, we aim to investigate how collaborative signals among learners contribute to the diagnosis of human cognitive states (i. e., knowledge proficiency) in the context of intelligent education.
A Survey of Models for Cognitive Diagnosis: New Developments and Future Directions
Cognitive diagnosis has been developed for decades as an effective measurement tool to evaluate human cognitive status such as ability level and knowledge mastery.
Event Grounded Criminal Court View Generation with Cooperative (Large) Language Models
Then, we incorporate the extracted events into court view generation by merging case facts and events.
Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery
Since existing methods still suffer from adopting the shortcuts in data to compose rationales and limited large-scale annotated rationales by human, in this paper, we propose a Shortcuts-fused Selective Rationalization (SSR) method, which boosts the rationalization by discovering and exploiting potential shortcuts.
Cooperative Classification and Rationalization for Graph Generalization
To address these challenges, in this paper, we propose a Cooperative Classification and Rationalization (C2R) method, consisting of the classification and the rationalization module.
FedGT: Federated Node Classification with Scalable Graph Transformer
However, existing methods have the following limitations: (1) The links between local subgraphs are missing in subgraph federated learning.
Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives
Consequently, we refine the cognitive states of cold-start students as diagnostic outcomes via virtual data, aligning with the diagnosis-oriented goal.
ASSIST: Interactive Scene Nodes for Scalable and Realistic Indoor Simulation
We present ASSIST, an object-wise neural radiance field as a panoptic representation for compositional and realistic simulation.
FedJudge: Federated Legal Large Language Model
To this end, in this paper, we propose the first Federated Legal Large Language Model (FedJudge) framework, which fine-tunes Legal LLMs efficiently and effectively.
