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cs.CL2026

Solar Open 2 Technical Report

Sungrae Park, Sanghoon Kim, Gyoungjin Gim +50

We present Solar Open 2, a 250B-A15B Mixture-of-Experts language model built for long-horizon agentic tasks, scaled up from Solar Open 1 (Solar Open 100B). To hold entire agent tra…

cs.CL2026

Knowledge Integration Decay in Search-Augmented Reasoning of Large Language Models

Sangwon Yu, Ik-hwan Kim, Donghun Kang +6

Modern Large Language Models (LLMs) have demonstrated remarkable capabilities in complex tasks by employing search-augmented reasoning to incorporate external knowledge into long c…

cs.CL2025

A Multifaceted Analysis of Negative Bias in Large Language Models through the Lens of Parametric Knowledge

Jongyoon Song, Sangwon Yu, Sungroh Yoon

Negative bias refers to the tendency of large language models (LLMs) to excessively generate negative responses in binary decision tasks (e.g., yes-no question answering). Previous…

cs.CL2025

Unleashing Multi-Hop Reasoning Potential in Large Language Models through Repetition of Misordered Context

Sangwon Yu, Ik-hwan Kim, Jongyoon Song +3

Multi-hop reasoning, which requires multi-step reasoning based on the supporting documents within a given context, remains challenging for large language models (LLMs). LLMs often…

cs.CL2025

Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment

Sangwon Yu, Jongyoon Song, Bongkyu Hwang +7

A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of…

cs.CL2024

Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination

Jongyoon Song, Sangwon Yu, Sungroh Yoon

In this paper, we identify a new category of bias that induces input-conflicting hallucinations, where large language models (LLMs) generate responses inconsistent with the content…