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arXiv:2602.21652v1 Announce Type: new Abstract: Large language models have demonstrated capabilities in text generation, while their increasing parameter scales present challenges in computational and memory …
arXiv:2602.21669v1 Announce Type: new Abstract: Knowledge Distillation (KD) has emerged as a crucial technique for compressing Large Language Models (LLMs). Although existing cross-tokenizer KD methods …
arXiv:2602.21720v1 Announce Type: new Abstract: Human recursive numeral systems (i.e., counting systems such as English base-10 numerals), like many other grammatical systems, are highly regular. …
arXiv:2602.21728v1 Announce Type: new Abstract: The reasoning process of Large Language Models (LLMs) is often plagued by hallucinations and missing facts in question-answering tasks. A …
arXiv:2602.21741v1 Announce Type: new Abstract: We describe our end-to-end system for Bengali long-form speech recognition (ASR) and speaker diarization submitted to the DL Sprint 4.0 …
arXiv:2602.21763v1 Announce Type: new Abstract: Implicit Discourse Relation Recognition (IDRR) remains a challenging task due to the requirement for deep semantic understanding in the absence …
arXiv:2602.21786v1 Announce Type: new Abstract: Chain-of-Thought (CoT) distillation from Large Language Models (LLMs) often induces "overthinking" in Small Language Models (SLMs), leading to performance degradation …
arXiv:2602.21854v1 Announce Type: new Abstract: As multimodal large language models (MLLMs) advance in handling interleaved image-text data, assessing their few-shot learning capabilities remains an open …
arXiv:2602.21862v1 Announce Type: new Abstract: Since individuals may struggle to recall all life details and often confuse events, establishing a system to assist users in …
arXiv:2602.21887v1 Announce Type: new Abstract: Current large reasoning models (LRMs) have shown strong ability on challenging tasks after reinforcement learning (RL) based post-training. However, previous …
arXiv:2602.21933v1 Announce Type: new Abstract: Sarcasm detection in multilingual and code-mixed environments remains a challenging task for natural language processing models due to structural variations, …
arXiv:2602.21941v1 Announce Type: new Abstract: Multimodal Role-Playing Agents (MRPAs) are attracting increasing attention due to their ability to deliver more immersive multimodal emotional interactions. However, …