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arXiv:2602.01202v1 Announce Type: new Abstract: The rapid evolution of agentic workflows has demonstrated strong performance of LLM-based agents in addressing complex reasoning tasks. However, existing...
arXiv:2602.01203v1 Announce Type: new Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several...
arXiv:2602.01204v1 Announce Type: new Abstract: Reinforcement learning (RL) has emerged as a dominant paradigm for eliciting long-horizon reasoning in Large Language Models (LLMs). However, scaling...
arXiv:2602.01206v1 Announce Type: new Abstract: The rapid advancement of generative artificial intelligence has enabled models capable of producing complex textual and visual outputs; however, their...
arXiv:2602.01207v1 Announce Type: new Abstract: Preference-based alignment is pivotal for training large reasoning models; however, standard methods like Direct Preference Optimization (DPO) typically treat all...
arXiv:2602.01208v1 Announce Type: new Abstract: Test-Time Scaling (TTS) has emerged as an effective paradigm for improving the reasoning performance of large language models (LLMs). However,...
arXiv:2602.01212v1 Announce Type: new Abstract: In this work, we revisit Transformer optimization through the lens of second-order geometry and establish a direct connection between architectural...
arXiv:2602.01213v1 Announce Type: new Abstract: Competitive games pose steep learning curves and strong social pressures, often discouraging novice players and limiting sustained engagement. To address...
arXiv:2602.01217v1 Announce Type: new Abstract: User-driven privacy allows individuals to control whether and at what granularity their data is shared, leading to datasets that mix...
arXiv:2602.01219v1 Announce Type: new Abstract: The attention operator in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically instantiated from input...
arXiv:2602.01221v1 Announce Type: new Abstract: The determinisation problem for min-plus (tropical) weighted automata was recently shown to be decidable. However, the proof is purely existential,...
arXiv:2602.01222v1 Announce Type: new Abstract: Small Language Models (SLMs) are attractive for cost-sensitive and resource-limited settings due to their efficient, low-latency inference. However, they often...
arXiv:2602.01225v1 Announce Type: new Abstract: Secure data join enables two parties with vertically distributed data to securely compute the joined table, allowing the parties to...
arXiv:2602.01226v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) swarms offer versatile applications in logistics, agriculture, and surveillance, yet controlling them requires expert knowledge for...
arXiv:2602.01227v1 Announce Type: new Abstract: The transition from fitting empirical data to achieving true human utility is fundamentally constrained by a granularity mismatch, where fine-grained...
arXiv:2602.01229v1 Announce Type: new Abstract: Bluetooth Low Energy (BLE) CTE transmissions provide in-phase and quadrature (IQ) samples whose empirical statistics are strongly governed by the...
arXiv:2602.01231v1 Announce Type: new Abstract: Online platforms increasingly offer "paid" ad-free subscriptions as an alternative to the traditional "free" ad-based model. The transition to ad-free...
arXiv:2602.01232v1 Announce Type: new Abstract: Diffusion of information, innovation, and ideas is an important phenomenon in social networks. Information propagates through the network and reaches...
arXiv:2602.01233v1 Announce Type: new Abstract: Training efficiency in large-scale models is typically assessed through memory consumption, training time, and model performance. Current methods often exhibit...
arXiv:2602.01237v1 Announce Type: new Abstract: Large language models (LLMs) achieve state-of-the-art accuracy on complex reasoning tasks by generating multiple chain-of-thought (CoT) traces, but using a...
arXiv:2602.01239v1 Announce Type: new Abstract: Despite extensive research on a wide range of question answering (QA) systems, most existing work focuses on answer containment-i.e., assuming...
arXiv:2602.01240v1 Announce Type: new Abstract: Zero-shot methods detect LLM-generated text by computing statistical signatures using a surrogate model. Existing approaches typically employ a fixed surrogate...
arXiv:2602.01244v1 Announce Type: new Abstract: Training agentic models for terminal-based tasks critically depends on high-quality terminal trajectories that capture realistic long-horizon interactions across diverse domains....
arXiv:2602.01246v1 Announce Type: new Abstract: Reasoning-focused Question Answering (QA) has advanced rapidly with Large Language Models (LLMs), yet high-quality benchmarks for low-resource languages remain scarce....