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Found 8 papers, 4 papers with code
Mitigating Boundary Ambiguity and Inherent Bias for Text Classification in the Era of Large Language Models
Our approach is grounded in the empirical observation that pairwise comparisons can effectively alleviate boundary ambiguity and inherent bias.
Position Debiasing Fine-Tuning for Causal Perception in Long-Term Dialogue
The core of the dialogue system is to generate relevant, informative, and human-like responses based on extensive dialogue history.
Reinforcement Learning with Token-level Feedback for Controllable Text Generation
To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs).
Joint Multi-Facts Reasoning Network For Complex Temporal Question Answering Over Knowledge Graph
Temporal Knowledge Graph (TKG) is an extension of regular knowledge graph by attaching the time scope.
Detection-based Intermediate Supervision for Visual Question Answering
Recently, neural module networks (NMNs) have yielded ongoing success in answering compositional visual questions, especially those involving multi-hop visual and logical reasoning.
Enhancing Low-Resource Relation Representations through Multi-View Decoupling
Recently, prompt-tuning with pre-trained language models (PLMs) has demonstrated the significantly enhancing ability of relation extraction (RE) tasks.
TREA: Tree-Structure Reasoning Schema for Conversational Recommendation
TREA constructs a multi-hierarchical scalable tree as the reasoning structure to clarify the causal relationships between mentioned entities, and fully utilizes historical conversations to generate more reasonable and suitable responses for recommended results.
PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking
This paper describes the PASH participation in TREC 2021 Deep Learning Track.
