8 papers
Rethinking Reward Models for Multi-Domain Test-Time Scaling
Dong Bok Lee, Seanie Lee, Sangwoo Park +12
The reliability of large language models (LLMs) during test-time scaling is often assessed with \emph{external verifiers} or \emph{reward models} that distinguish correct reasoning…
MacroLens: A Multi-Task Benchmark for Contextual Financial Reasoning under Macroeconomic Scenarios
Patara Trirat, Jin Myung Kwak, Jay Heo +2
Financial decision-making is contextual: forecasting prices, valuing companies, and assessing event exposure weigh price history, accounting fundamentals, macroeconomic regime, and…
OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources
Jinheon Baek, Soyeong Jeong, Sangwoo Park +5
Real-world information needs require access to structurally diverse knowledge sources, from unstructured text and relational tables to knowledge graphs and property graphs. Existin…
TS-Debate: Multimodal Collaborative Debate for Zero-Shot Time Series Reasoning
Patara Trirat, Jin Myung Kwak, Jay Heo +2
Recent progress at the intersection of large language models (LLMs) and time series (TS) analysis has revealed both promise and fragility. While LLMs can reason over temporal struc…
Delta Attention: Fast and Accurate Sparse Attention Inference by Delta Correction
Jeffrey Willette, Heejun Lee, Sung Ju Hwang
The attention mechanism of a transformer has a quadratic complexity, leading to high inference costs and latency for long sequences. However, attention matrices are mostly sparse,…
Training-Free Exponential Context Extension via Cascading KV Cache
Jeffrey Willette, Heejun Lee, Youngwan Lee +2
The transformer's context window is vital for tasks such as few-shot learning and conditional generation as it preserves previous tokens for active memory. However, as the context…