arXiv:2603.23949v1 Announce Type: new
Abstract: Argument Mining(AM) aims to uncover the argumentative structures within a text. Previous methods require several subtasks, such as span identification, component classification, and relation classificati…
arXiv:2603.23938v1 Announce Type: new
Abstract: Most testbeds for omni-modal models assess multimodal understanding via textual outputs, leaving it unclear whether these models can properly speak their answers. To study this, we introduce OmniACBench,…
arXiv:2603.23848v1 Announce Type: new
Abstract: LLMs are increasingly used as long-running conversational agents, yet every major benchmark evaluating their memory treats user information as static facts to be stored and retrieved. That’s the wrong mo…
arXiv:2603.24579v1 Announce Type: new
Abstract: Hallucination remains a critical bottleneck for large language models (LLMs), undermining their reliability in real-world applications, especially in Retrieval-Augmented Generation (RAG) systems. While e…
arXiv:2603.23844v1 Announce Type: new
Abstract: Recent work shows overwhelming evidence that LLMs, even those trained to scale their reasoning trace, perform unsatisfactorily when solving planning problems too complex. Whether the same conclusion hold…
arXiv:2603.24536v1 Announce Type: new
Abstract: Reading comprehension presents a significant challenge for children with Special Educational Needs and Disabilities (SEND), often requiring intensive one-on-one reading support. To assist therapists in s…
arXiv:2603.23797v1 Announce Type: new
Abstract: Children in many parts of the world hear relatively little speech directed to them, yet still reach major language development milestones. What differs about the speech input that infants learn from when…
arXiv:2603.12252v3 Announce Type: replace-cross
Abstract: Recently, Multimodal Large Language Models (MLLMs) have been widely integrated into diffusion frameworks primarily as text encoders to tackle complex tasks such as spatial reasoning. However, t…
arXiv:2603.23750v1 Announce Type: new
Abstract: Large language models are increasingly consulted for Islamic knowledge, yet no comprehensive benchmark evaluates their performance across core Islamic disciplines. We introduce IslamicMMLU, a benchmark o…
arXiv:2603.19311v2 Announce Type: replace
Abstract: Prompt engineering is effective but labor-intensive, motivating automated optimization methods. Existing methods typically require labeled datasets, which are often unavailable, and produce verbose, …