8 papers · 1 filter
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…
ES-Merging: Biological MLLM Merging via Embedding Space Signals
Wonbin Lee, Dongki Kim, Sung Ju Hwang
Biological multimodal large language models (MLLMs) have emerged as powerful foundation models for scientific discovery. However, existing models are specialized to a single modali…
Learn from Weaknesses: Automated Domain Specialization for Small Computer-Use Agents
Suji Kim, Kangsan Kim, Sung Ju Hwang
Computer-use agents (CUAs) have recently made substantial progress, but deploying a separate large expert for each software domain remains expensive. Small open computer-use agents…
It Takes Two: Complementary Self-Distillation for Contextual Integrity in LLMs
Sangwoo Park, Woongyeong Yeo, Seanie Lee +6
Contextual Integrity (CI) defines privacy not merely as keeping information hidden, but as governing information flows according to the norms of a given context. As large language…
HINT-SD: Targeted Hindsight Self-Distillation for Long-Horizon Agents
Woongyeng Yeo, Yumin Choi, Taekyung Ki +1
Training long-horizon LLM agents with reinforcement learning is challenging because sparse outcome rewards reveal whether a task succeeds, but not which intermediate actions caused…
SAGE: Shaping Anchors for Guided Exploration in RLVR of LLMs
Chanuk Lee, Minki Kang, Sung Ju Hwang
Recent studies observe that reinforcement learning with verifiable rewards (RLVR) reliably improves pass@1 on reasoning tasks, yet often fails to yield comparable gains in pass@k,…