1 citations · 1 across the 7 of their papers we have counts for
5 papers · 1 filter
WHALE: A Simple Recipe for Joint Harness-Weight Optimization
Haechan Kim, Yoonho Lee, Gisang Lee +2
Agent performance depends jointly on the model parameters and the executable harness code that manages context and control flow. Optimizing either component in isolation can leave…
Pruning and Distilling Mixture-of-Experts into Dense Language Models
Junhyuck Kim, Jihun Yun, Haechan Kim +3
Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory, making it less preferable for…
KVoiceBench, KOpenAudioBench, and KMMAU: Agent-Driven Korean Speech Benchmarks for Evaluating SpeechLMs
Haechan Kim, Seungjun Chung, Inkyu Park +2
Speech language models (SpeechLMs) have achieved substantial progress by extending large language models (LLMs) to the speech modality. However, SpeechLM evaluation remains heavily…
Raon-Speech Technical Report
Beomsoo Kim, Changho Choi, Dohyun Kim +23
We present Raon-Speech, a top-performing 9B-parameter speech language model (SpeechLM) for English and Korean speech understanding, answering, and generation, and Raon-SpeechChat,…
Discounted Beta-Bernoulli Reward Estimation for Sample-Efficient Reinforcement Learning with Verifiable Rewards
Haechan Kim, Soohyun Ryu, Gyouk Chu +2
Reinforcement learning with verifiable rewards (RLVR) has emerged as an effective post-training paradigm for improving the reasoning capabilities of large language models. However,…