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전체 전문분석자료
arXiv:2603.12932v1 Announce Type: new Abstract: Adapting Large Language Models (LLMs) to specialized domains requires high-quality instruction tuning datasets, which are expensive to create through human …
arXiv:2603.12963v1 Announce Type: new Abstract: The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to …
arXiv:2603.12983v1 Announce Type: new Abstract: Error Span Detection (ESD) is a crucial subtask in Machine Translation (MT) evaluation, aiming to identify the location and severity …
arXiv:2603.13038v1 Announce Type: new Abstract: Supervised Semantic Differential (SSD) is a mixed quantitative-interpretive method that models how text meaning varies with continuous individual-difference variables by …
arXiv:2603.13045v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capability in machine translation on high-resource language pairs, yet their performance on low-resource …
arXiv:2603.13154v1 Announce Type: new Abstract: As corporate responsibility increasingly incorporates environmental, social, and governance (ESG) criteria, ESG reporting is becoming a legal requirement in many …
arXiv:2603.13201v1 Announce Type: new Abstract: Instruction Tuning (IT) has been proven to be an effective approach to unlock the powerful capabilities of large language models …
arXiv:2603.12274v1 Announce Type: cross Abstract: Venture capital (VC) investors face a large number of investment opportunities but only invest in few of these, with even …
arXiv:2603.12368v1 Announce Type: cross Abstract: Generative retrieval (GR) models encode a corpus within model parameters and generate relevant document identifiers directly for a given query. …
arXiv:2603.12378v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) techniques, particularly Low-Rank Adaptation (LoRA), have become essential for adapting Large Language Models (LLMs) to downstream tasks. …
arXiv:2603.12554v1 Announce Type: cross Abstract: Reinforcement learning (RL) has been effective for post-training autoregressive (AR) language models, but extending these methods to diffusion language models …
arXiv:2603.12565v1 Announce Type: cross Abstract: SpeechLLMs typically combine ASR-trained encoders with text-based LLM backbones, leading them to inherit written-style output patterns unsuitable for text-to-speech synthesis. …