Poster Session 1
Time: 15:00-16:30, 17 Nov, Monday
Venue: TOPAZ + OPAL
| No. | Poster Index | Paper ID | Paper Title |
| 1 | A-1 | 23 | Federated Financial Reasoning Distillation: Training A Small Financial Expert by Learning From Multiple Teachers |
| 2 | A-2 | 24 | Regret-Optimized Portfolio Enhancement through Deep Reinforcement Learning and Future Looking Rewards |
| 3 | A-3 | 29 | Leveraging Deep Learning Optimization for Monte Carlo Calibration of (Rough) Stochastic Volatility Models |
| 4 | A-4 | 32 | Norm-Salvaged Embedding: Improving Condition Alignment of Synthetic Time Series Generation in Finance |
| 5 | A-5 | 33 | IKNet: Interpretable Stock Price Prediction via Keyword-Guided Integration of News and Technical Indicators |
| 6 | A-6 | 34 | Extracting the Structure of Press Releases for Predicting Earnings Announcement Returns |
| 7 | A-7 | 35 | A Role-Aware Multi-Agent Framework for Financial Education QA with LLMs |
| 8 | A-8 | 58 | Natural-gas storage modelling by deep reinforcement learning |
| 9 | A-9 | 66 | LENS: Large Pre-trained Transformer for Exploring Financial Time Series Regularities |
| 10 | A-10 | 70 | Is BTC Enough? A New Perspective on Cryptocurrency Price Formation |
| 11 | B-1 | 73 | Quantum Optimization of Currency Arbitrage via Graph-Informed Entanglement Strategies |
| 12 | B-2 | 78 | A Data-Driven Asset Relation Extraction and Portfolio Optimization Method through Convolution |
| 13 | B-3 | 80 | Unmasking Bias in Financial AI: A Robust Framework for Evaluating and Mitigating Hidden Biases in LLMs |
| 14 | B-4 | 88 | Constrained Tabular Diffusion for Finance |
| 15 | B-5 | 89 | Unified Item Segmentation for 10-Q and 10-K Filings Using Item-Aware Document-Level Auxiliary Tasks |
| 16 | B-6 | 90 | MacroVAE: Counterfactual Financial Scenario Generation via Macroeconomic Conditioning |
| 17 | B-7 | 93 | FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generation |
| 18 | B-8 | 94 | FinAgentBench: A Benchmark Dataset for Agentic Retrieval in Financial Question Answering |
| 19 | B-9 | 97 | Structured Agentic Workflows for Financial Time-Series Modelling with LLMs and Reflective Feedback |
| 20 | B-10 | 101 | FinResearchBench: A Logic Tree based Agent-as-a-Judge Evaluation Framework for Financial Research Agents |
| 21 | C-1 | 109 | Positive-Unlabeled Learning for Financial Misstatement Detection under Realistic Constraints |
| 22 | C-2 | 110 | FinDPO: Financial Sentiment Analysis for Algorithmic Trading through Preference Optimization of LLMs |
| 23 | C-3 | 114 | Vision, Voice, and Text: Pioneering Zero-shot Multimodal LLMs for Sentiment-driven Investment |
| 24 | C-4 | 119 | Optimizing Large Language Models for ESG Activity Detection in Financial Texts |
| 25 | C-5 | 129 | Adaptive Sample Weighting with Regime-Aware Meta-Learning Framework for Financial Forecasting |
| 26 | C-6 | 143 | FactorMAD: A Multi-Agent Debate Framework Based on Large Language Models for Interpretable Stock Alpha Factor Mining |
| 27 | C-7 | 155 | Arbitrage-Free Implied Volatility Surface Smoothing via Generative Adversarial Networks |
| 28 | C-8 | 161 | Multilingual BERT-based Classification and Recommendation Model for Supporting Innovation Finance Decisions |
| 29 | C-9 | 169 | CMS-VAE: A Strategy-aware Variational AutoEncoder for High-Fidelity Crypto Market Simulation |
| 30 | C-10 | 177 | Large Language Model Agents for Investment Management: Foundations, Benchmarks, and Research Frontiers |
Poster Session 2
Time: 15:00-16:30, 18 Nov, Tuesday
Venue: TOPAZ + OPAL
| No. | Poster Index | Paper ID | Paper Title |
| 1 | A-1 | 183 | Multi-Agent Reinforcement Learning for Market Making: Competition without Collusion |
| 2 | A-2 | 187 | Hypergraph Attention Network to Predict Stock Movements By Exploring Higher-order Relationships |
| 3 | A-3 | 188 | Learning to Trade with Preferences: Interpretable Execution via Mixture-of-Experts |
| 4 | A-4 | 190 | Predictive Uncertainty Quantification for Financial DNN Using Regular Vine Copula |
| 5 | A-5 | 195 | Robust time series generation via Schr\”{o}dinger Bridge: a comprehensive evaluation |
| 6 | A-6 | 211 | Learning to Scalp: A Reinforcement Learning Agent-Based Study |
| 7 | A-7 | 213 | Curriculum-Guided Reinforcement Learning for Synthesizing Gas-Efficient Financial Derivatives Contracts |
| 8 | A-8 | 215 | Contextual Time Series Embedding: A State Space Perspective for Financial Data |
| 9 | A-9 | 218 | Aligning Language Models with Investor and Market Behavior for Financial Recommendations |
| 10 | A-10 | 221 | Demystifying TCFD Disclosures: An AI-Powered Framework for Enhanced Transparency and Trust |
| 11 | B-1 | 224 | Fast Monitoring of Systemic Risk in Financial Networks with Credit Default Swaps |
| 12 | B-2 | 234 | Right Place, Right Time: Market Simulation-based RL for Execution Optimisation |
| 13 | B-3 | 241 | Time-Varying Factor-Augmented Models for Volatility Forecasting |
| 14 | B-4 | 243 | On the Potential of Tool-Enhanced Small Language Models to Match Large Models in Finance |
| 15 | B-5 | 361 | Language Models for Automated Market Commentary from Corporate Disclosures |
| 16 | B-6 | 268 | DiffVolume: Diffusion Models for Volume Generation in Limit Order Books |
| 17 | B-7 | 272 | From News to Returns: A Granger-Causal Hypergraph Transformer on the Sphere |
| 18 | B-8 | 276 | Fusing Narrative Semantics for Financial Volatility Forecasting |
| 19 | B-9 | 292 | Graph Learning for Foreign Exchange Rate Prediction and Statistical Arbitrage |
| 20 | B-10 | 337 | Mean Variance Efficient Collaborative Filtering for Stock Recommendations |
| 21 | C-1 | 338 | LatentGraph: From Latent States to Rule-based Expressions for Explainable Financial Forecasting |
| 22 | C-2 | 346 | Attention-Based Multi-Asset Order Flow Networks for Enhanced Mid-Price Prediction |
| 23 | C-3 | 347 | Shock-Biased Attention: Enhancing Transformer Hawkes Processes with Amplitude-Driven Temporal Kernels |
| 24 | C-4 | 349 | From Constituents to Index: Interpretable Price Movement Prediction via Cross-Asset Order Flow |
| 25 | C-5 | 354 | Data-Driven Trade Flow Decomposition for Exchange-Traded Funds and their Constituents |
| 26 | C-6 | 253 | Long-Term Financial Forecasting and Trading via Multi-Agent Reinforcement Learning |
| 27 | C-7 | 369 | Adaptive Quantum Channels as Long-Memory Generative Models |
ICAIF’25 features on-site poster sessions only. The size of the poster is A0, and posters need to be in Portrait format.
All posters will be displayed during the poster session, and presenting authors are expected to be present in person for discussions. If you’re the presenting author of your poster paper and cannot attend the conference in-person, you may personally ask a proxy to help you bring and mount your poster in the assigned poster panel. If you cannot find a proxy, please contact the student volunteer co-chair (Xinrun Wang, email: xrwang@smu.edu.sg), who will assist the printing and mount of posters.
ACM ICAIF'25 