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arXiv:2509.03148v2 Announce Type: replace Abstract: The Romansh language, spoken in Switzerland, has limited resources for machine translation evaluation. In this...
arXiv:2509.19231v1 Announce Type: cross Abstract: We present ChiReSSD, a speech reconstruction framework that preserves children speaker’s identity while suppressing mispronunciations....
arXiv:2509.19109v1 Announce Type: new Abstract: We introduce KyrgyzNER, the first manually annotated named entity recognition dataset for the Kyrgyz language....
arXiv:2509.18762v1 Announce Type: new Abstract: Large language models (LLMs) have achieved impressive performance across natural language processing (NLP) tasks. As...
arXiv:2506.09707v3 Announce Type: replace-cross Abstract: Prolonged Exposure (PE) therapy is an effective treatment for post-traumatic stress disorder (PTSD), but evaluating...
arXiv:2509.12955v2 Announce Type: replace Abstract: The automated generation of research workflows is essential for improving the reproducibility of research and...
arXiv:2507.13142v3 Announce Type: replace-cross Abstract: Modern language models address complex questions through chain-of-thought (CoT) reasoning (Wei et al., 2023) and...
arXiv:2509.17628v1 Announce Type: new Abstract: Large Language Models (LLMs) have excelled in question-answering (QA) tasks within single domains. However, their...
arXiv:2509.17437v1 Announce Type: new Abstract: Recent advancements in reinforcement learning (RL) have enhanced the reasoning abilities of large language models...
Beyond the Exploration-Exploitation Trade-off: A Hidden State Approach for LLM Reasoning in RLVR
Beyond Superficial Unlearning: Sharpness-Aware Robust Erasure of Hallucinations in Multimodal LLMs
Beyond single-model AI: How architectural design drives reliable multi-agent orchestration
Beyond Short-term Memory: The 3 Types of Long-term Memory AI Agents Need
Beyond Profile: From Surface-Level Facts to Deep Persona Simulation in LLMs
Beyond Multiple Choice: Evaluating Steering Vectors for Summarization
Beyond Modality Limitations: A Unified MLLM Approach to Automated Speaking Assessment with Effective Curriculum Learning
Beyond instruction-conditioning, MoTE: Mixture of Task Experts for Multi-task Embedding Models
Beyond Imitation: Recovering Dense Rewards from Demonstrations
Beyond Homogeneous Attention: Memory-Efficient LLMs via Fourier-Approximated KV Cache
Beyond GridSearchCV: Advanced Hyperparameter Tuning Strategies for Scikit-learn Models
