arXiv:2604.00694v1 Announce Type: cross Abstract: Autonomous agents increasingly interact with the web, yet most websites remain designed for human browsers — a fundamental mismatch that the emerging “Agentic Web” must resolve. Agents must repeatedly browse pages, inspect DOMs, and reverse-engineer callable routes — a process that is slow, brittle, and redundantly repeated across agents. We […]
Stochastic ordering tools for continuous-time Markov chains and applications to reaction network models
arXiv:2604.00756v1 Announce Type: cross Abstract: Stochastic reaction networks are mathematical models with a wide range of applications in biochemistry, ecology, and epidemiology, and are often complex to analyze. Except for some special cases, it is generally difficult to predict how the abundances of all considered species evolve over time. A possible approach to address this […]
NFC based inventory control system for secure and efficient communication
arXiv:2604.00181v1 Announce Type: cross Abstract: This paper brings up this idea of using Near Field Communication (NFC) for inventory control system instead of using traditional barcodes. NFC because of its high security, ease of use and efficiency can be very suitable for systems like inventory control. In traditional inventory control systems, each product has a […]
Ultrasonic Brain Computer Interfaces for Enhancing Human-Machine Cognition
arXiv:2604.00349v1 Announce Type: new Abstract: Low-intensity transcranial focused ultrasound (tFUS) is rapidly emerging as a transformative non-invasive brain stimulation (NIBS) modality characterized by high spatial resolution and ability to target deep brain circuits. Unlike electromagnetic techniques such as transcranial magnetic stimulation and transcranial direct current stimulation, which are constrained by centimeter-scale resolution and a depth-focality […]
HiMA-Ecom: Enabling Joint Training of Hierarchical Multi-Agent E-commerce Assistants
arXiv:2506.19846v2 Announce Type: replace Abstract: Hierarchical multi-agent systems based on large language models (LLMs) have become a common paradigm for building AI assistants in vertical domains such as e-commerce, where a master agent coordinates multiple specialized sub-agents. Despite their practical importance, realistic benchmarks for training and evaluating such systems remain scarce, and joint optimization across […]
Signals: Trajectory Sampling and Triage for Agentic Interactions
arXiv:2604.00356v1 Announce Type: new Abstract: Agentic applications based on large language models increasingly rely on multi-step interaction loops involving planning, action execution, and environment feedback. While such systems are now deployed at scale, improving them post-deployment remains challenging. Agent trajectories are voluminous and non-deterministic, and reviewing each one, whether through human review or auxiliary LLMs, […]
When Agents Persuade: Rhetoric Generation and Mitigation in LLMs
arXiv:2603.04636v2 Announce Type: replace Abstract: Despite their wide-ranging benefits, LLM-based agents deployed in open environments can be exploited to produce manipulative material. In this study, we task LLMs with propaganda objectives and analyze their outputs using two domain-specific models: one that classifies text as propaganda or non-propaganda, and another that detects rhetorical techniques of propaganda […]
In harmony with gpt-oss
arXiv:2604.00362v1 Announce Type: new Abstract: No one has independently reproduced OpenAI’s published scores for gpt-oss-20b with tools, because the original paper discloses neither the tools nor the agent harness. We reverse-engineered the model’s in-distribution tools: when prompted without tool definitions, gpt-oss still calls tools from its training distribution with high statistical confidence — a strong […]
Situationally-Aware Dynamics Learning
arXiv:2505.19574v3 Announce Type: replace-cross Abstract: Autonomous robots operating in complex, unstructured environments face significant challenges due to latent, unobserved factors that obscure their understanding of both their internal state and the external world. Addressing this challenge would enable robots to develop a more profound grasp of their operational context. To tackle this, we propose a […]
How to Forage for a Mate?
arXiv:2604.00393v1 Announce Type: new Abstract: Foraging is a central decision-making behavior performed by all animals, essential to garnishing enough energy for an organism to survive. Similarly, mating is crucial for evolutionary continuity and offspring production. Mate choice is one of the central tenets of sexual selection, driving major evolutionary processes, and can be regarded as […]
E-Scores for (In)Correctness Assessment of Generative Model Outputs
arXiv:2510.25770v2 Announce Type: replace-cross Abstract: While generative models, especially large language models (LLMs), are ubiquitous in today’s world, principled mechanisms to assess their (in)correctness are limited. Using the conformal prediction framework, previous works construct sets of LLM responses where the probability of including an incorrect response, or error, is capped at a user-defined tolerance level. […]
Decision-Centric Design for LLM Systems
arXiv:2604.00414v1 Announce Type: new Abstract: LLM systems must make control decisions in addition to generating outputs: whether to answer, clarify, retrieve, call tools, repair, or escalate. In many current architectures, these decisions remain implicit within generation, entangling assessment and action in a single model call and making failures hard to inspect, constrain, or repair. We […]