7 citations · 11 across the 8 of their papers we have counts for
8 papers
Think in English, Answer in Korean: Efficient Adaptation of Multilingual Tool-Using Agents
Utsav Garg, Sungjin Hong, Jason Jung +6
We present LuckyStar 111B, a 111B-parameter hybrid reasoning model developed through a collaboration between Cohere and LG CNS for Korean-English enterprise agents under practical…
ICaRus: Identical Cache Reuse for Efficient Multi Model Inference
Sunghyeon Woo, Jaeeun Kil, Hoseung Kim +9
Multi model inference has recently emerged as a prominent paradigm, particularly in the development of agentic AI systems. However, in such scenarios, each model must maintain its…
PrefillShare: A Shared Prefill Module for KV Reuse in Multi-LLM Disaggregated Serving
Sunghyeon Woo, Hoseung Kim, Sunghwan Shim +9
Multi-agent systems increasingly orchestrate multiple specialized language models to solve complex real-world problems, often invoking them over a shared context. This execution pa…
Chopping Trees: Semantic Similarity Based Dynamic Pruning for Tree-of-Thought Reasoning
Joongho Kim, Xirui Huang, Zarreen Reza +1
Tree-of-Thought (ToT) reasoning boosts the problem-solving abilities of Large Language Models (LLMs) but is computationally expensive due to semantic redundancy, where distinct bra…
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
HyperCLOVA X Technical Report
Kang Min Yoo, Jaegeun Han, Sookyo In +393
We introduce HyperCLOVA X, a family of large language models (LLMs) tailored to the Korean language and culture, along with competitive capabilities in English, math, and coding. H…
CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists
Yukyung Lee, Joonghoon Kim, Jaehee Kim +4
Existing LLM-as-a-Judge approaches for evaluating text generation suffer from rating inconsistencies, with low agreement and high rating variance across different evaluator models.…
Which is better? Exploring Prompting Strategy For LLM-based Metrics
Joonghoon Kim, Saeran Park, Kiyoon Jeong +4
This paper describes the DSBA submissions to the Prompting Large Language Models as Explainable Metrics shared task, where systems were submitted to two tracks: small and large sum…