Yixuan Tang

Orcid: 0009-0006-2405-2026

Affiliations:
  • Hong Kong University of Science and Technology, Department of ISOM, Hong Kong


According to our database1, Yixuan Tang authored at least 17 papers between 2023 and 2026.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Mind the Shift: Decoding Monetary Policy Stance from FOMC Statements with Large Language Models.
CoRR, March, 2026

KV-Embedding: Training-free Text Embedding via Internal KV Re-routing in Decoder-only LLMs.
CoRR, January, 2026

2025
SR-GRPO: Stable Rank as an Intrinsic Geometric Reward for Large Language Model Alignment.
CoRR, December, 2025

GAPrune: Gradient-Alignment Pruning for Domain-Aware Embeddings.
CoRR, September, 2025

PersonaFuse: A Personality Activation-Driven Framework for Enhancing Human-LLM Interactions.
CoRR, September, 2025

Revealing the Numeracy Gap: An Empirical Investigation of Text Embedding Models.
CoRR, September, 2025

Adversarial Mixup Unlearning.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

FinMTEB: Finance Massive Text Embedding Benchmark.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Evaluating and Aligning Human Economic Risk Preferences in LLMs.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

Know the Unknown: An Uncertainty-Sensitive Method for LLM Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Do We Need Domain-Specific Embedding Models? An Empirical Investigation.
CoRR, 2024

Pooling And Attention: What Are Effective Designs For LLM-Based Embedding Models?
CoRR, 2024

MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries.
CoRR, 2024

Exploring the Relationship between In-Context Learning and Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
FinEntity: Entity-level Sentiment Classification for Financial Texts.
CoRR, 2023

InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning.
CoRR, 2023

FinEntity: Entity-level Sentiment Classification for Financial Texts.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023


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