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arXiv:2602.10289v1 Announce Type: new Abstract: Robots operating in unstructured human environments inevitably encounter failures, especially in robot caregiving scenarios. While humans can often help robots...
arXiv:2602.10290v1 Announce Type: new Abstract: We study the computational complexity of strategic behaviour in primary elections. Unlike direct voting systems, primaries introduce a multi-stage process...
arXiv:2602.10295v1 Announce Type: new Abstract: ECHO (Evaluation of Chat, Human behavior, and Outcomes) is an open research platform designed to support reproducible, mixed-method studies of...
arXiv:2602.10296v1 Announce Type: new Abstract: We study the problem of finding an $\epsilon$-fixed point of a contraction map $f:[0,1]^k\mapsto[0,1]^k$ under both the $\ell_\infty$-norm and the...
arXiv:2602.10298v1 Announce Type: new Abstract: This paper investigates whether LMs recruit shared computational mechanisms for general Theory of Mind (ToM) and language-specific pragmatic reasoning in...
arXiv:2602.10299v1 Announce Type: new Abstract: Recent work on network attacks have demonstrated that ML-based network intrusion detection systems (NIDS) can be evaded with adversarial perturbations....
arXiv:2602.10300v1 Announce Type: new Abstract: Researchers build scaling laws to forecast the training performance of expensive large-scale runs with larger model size N and data...
arXiv:2602.10301v1 Announce Type: new Abstract: Among the different concepts for wave energy conversion, oscillating surge wave energy converters have been shown to have a high...
arXiv:2602.10303v1 Announce Type: new Abstract: Predicting time-to-event outcomes when event times are interval censored is challenging because the exact event time is unobserved. Many existing...
arXiv:2602.10304v1 Announce Type: new Abstract: While cervical arthroplasty using Total Disc Replacement (TDR) implants is an established treatment for persistent neck and arm pain, revision...
arXiv:2602.10305v1 Announce Type: new Abstract: Reward shaping has been applied widely to accelerate Reinforcement Learning (RL) agents' training. However, a principled way of designing effective...
arXiv:2602.10312v1 Announce Type: new Abstract: R2RAG-Flood is a reasoning-reinforced, training-free retrieval-augmented generation framework for post-storm property damage nowcasting. Building on an existing supervised tabular predictor,...
arXiv:2602.10314v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) have emerged as a promising approach for generative modeling in discrete spaces. By generating sequences in...
arXiv:2602.10319v1 Announce Type: new Abstract: Recently, adversarial attacks for diffusion models as well as their fine-tuning process have been developed rapidly. To prevent the abuse...
arXiv:2602.10320v1 Announce Type: new Abstract: Global protocols specify distributed, message-passing protocols from a birds-eye view, and are used as a specification for synthesizing local implementations....
arXiv:2602.10321v1 Announce Type: new Abstract: Retrieving known items from vague descriptions, Tip-of-the-Tongue (ToT) retrieval, remains a significant challenge. We propose using a single call to...
arXiv:2602.10324v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in social and strategic scenarios, it becomes critical to understand where and...
arXiv:2602.10326v1 Announce Type: new Abstract: Despite the remarkable success of sampling-based generative models such as flow matching, they can still produce samples of inconsistent or...
arXiv:2602.10329v1 Announce Type: new Abstract: Human reasoning is shaped by resource rationality -- optimizing performance under constraints. Recently, inference-time scaling has emerged as a powerful...
arXiv:2602.10337v1 Announce Type: new Abstract: The online bisection problem requires maintaining a dynamic partition of $n$ nodes into two equal-sized clusters. Requests arrive sequentially as...
arXiv:2602.10343v1 Announce Type: new Abstract: Recent advances in generative image models have enabled the creation of highly realistic political deepfakes, posing risks to information integrity,...
arXiv:2602.10344v1 Announce Type: new Abstract: In coherent imaging, speckle is statistically modeled as multiplicative noise, posing a fundamental challenge for image reconstruction. While maximum likelihood...
arXiv:2602.10345v1 Announce Type: new Abstract: We present a scalable, AI-powered system that identifies and extracts evidence-based behavioral nudges from unstructured biomedical literature. Nudges are subtle,...
arXiv:2602.10346v1 Announce Type: new Abstract: Large language models (LLMs) must balance diversity and creativity against logical coherence in open-ended generation. Existing truncation-based samplers are effective...