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arXiv:2603.18273v1 Announce Type: new Abstract: In this technical report, we present the Educational Data Mining Automated Research System (EDM-ARS), a domain-specific multi-agent pipeline that automates …
arXiv:2603.18436v1 Announce Type: new Abstract: Neuro-symbolic artificial intelligence (AI) systems typically couple a neural perception module to a discrete symbolic solver through a non-differentiable boundary, …
arXiv:2603.18197v1 Announce Type: new Abstract: Recent studies reveal gaps in delegating critical tasks to agentic AI that accesses websites on the user's behalf, primarily due …
arXiv:2603.18528v1 Announce Type: new Abstract: Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. …
arXiv:2603.18662v1 Announce Type: new Abstract: Geometric reasoning inherently requires "thinking with constructions" -- the dynamic manipulation of visual aids to bridge the gap between problem …
arXiv:2603.18010v1 Announce Type: new Abstract: The production of large-scale political datasets typically demands extracting structured facts from vast piles of unstructured documents or web sources, …
arXiv:2603.18676v1 Announce Type: new Abstract: MANAR (Memory-augmented Attention with Navigational Abstract Conceptual Representation), contextualization layer generalizes standard multi-head attention (MHA) by instantiating the principles of …
arXiv:2603.18014v1 Announce Type: new Abstract: Structured Outputs from current LLMs exhibit sporadic errors, hindering enterprise AI efforts from realizing their immense potential. We present CONSTRUCT, …
arXiv:2603.18614v1 Announce Type: new Abstract: Tool-augmented large language models (LLMs) must tightly couple multi-step reasoning with external actions, yet existing benchmarks often confound this interplay …
arXiv:2603.18420v1 Announce Type: new Abstract: Embedding models group text by semantic content, what text is about. We show that temporal co-occurrence within texts discovers a …
arXiv:2603.18627v1 Announce Type: new Abstract: Precise Text-to-Image (T2I) generation has achieved great success but is hindered by the limited relational reasoning of static text encoders …
arXiv:2603.18656v1 Announce Type: new Abstract: Multimodal reasoning in vision-language models (VLMs) typically relies on a two-stage process: supervised fine-tuning (SFT) and reinforcement learning (RL). In …