2 citations · 5 across the 12 of their papers we have counts for
5 papers · 1 filter
AI PB: A Grounded Generative Agent for Personalized Investment Insights
Daewoo Park, Suho Park, Inseok Hong +5
We present AI PB, a production-scale generative agent deployed in real retail finance. Unlike reactive chatbots that answer queries passively, AI PB proactively generates grounded,…
NMIXX: Domain-Adapted Neural Embeddings for Cross-Lingual eXploration of Finance
Hanwool Lee, Sara Yu, Yewon Hwang +4
Financial text embeddings must distinguish changes in event status, perspective, and obligations even when passages share similar wording. NMIXX adapts existing encoders through 18…
TWICE: What Advantages Can Low-Resource Domain-Specific Embedding Model Bring? -- A Case Study on Korea Financial Texts
Yewon Hwang, Sungbum Jung, Hanwool Lee +1
Domain specificity of embedding models is critical for effective performance. However, existing benchmarks, such as FinMTEB, are primarily designed for high-resource languages, lea…
(G)I-DLE: Generative Inference via Distribution-preserving Logit Exclusion with KL Divergence Minimization for Constrained Decoding
Hanwool Lee
We propose (G)I-DLE, a new approach to constrained decoding that leverages KL divergence minimization to preserve the intrinsic conditional probability distribution of autoregressi…
Redefining Evaluation Standards: A Unified Framework for Evaluating the Korean Capabilities of Language Models
Hanwool Lee, Dasol Choi, Sooyong Kim +6
Recent advancements in Korean large language models (LLMs) have driven numerous benchmarks and evaluation methods, yet inconsistent protocols cause up to 10 p.p performance gaps ac…