10 papers
SWE-Router: Routing in Multi-turn Agentic Software Engineering Tasks
Seongho Son, Sangwoong Yoon, Jiahua Tang +3
Large language models (LLMs) embedded in multi-turn agentic harnesses are reshaping software engineering (SWE), but routing every task to a frontier model is wasteful when many iss…
GDSD: Reinforcement Learning as Guided Denoiser Self-Distillation for Diffusion Language Models
Xiaohang Tang, Keyue Jiang, Che Liu +4
Reinforcement learning (RL) can be used to improve the policy (denoiser) of diffusion large language models (dLLMs), while being hindered by the intractability of the policy likeli…
Bridging Language Models and Financial Analysis
Alejandro Lopez-Lira, Jihoon Kwon, Sangwoon Yoon +2
The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector. Financia…
MATE: Solving Contextual Markov Decision Processes with Memory of Accumulated Transition Embeddings
Himchan Hwang, Hyeokju Jeong, Gene Chung +3
We propose MATE, a simple yet effective memory architecture for solving Contextual Markov Decision Processes (CMDPs), a family of MDPs parameterized by an unobserved context. In CM…
Focus Matters: Phase-Aware Suppression for Hallucination in Vision-Language Models
Sohyeon Kim, Sang Yeon Yoon, Kyeongbo Kong
Large Vision-Language Models (LVLMs) have achieved impressive progress in multimodal reasoning, yet they remain prone to object hallucinations, generating descriptions of objects t…
Robust Multi-Objective Controlled Decoding of Large Language Models
Seongho Son, William Bankes, Sangwoong Yoon +3
We introduce Robust Multi-Objective Decoding (RMOD), a novel inference-time algorithm that robustly aligns Large Language Models (LLMs) to multiple human objectives (e.g., instruct…