arXiv:2511.10532v1 Announce Type: cross Abstract: Repetitive strain injury (RSI) affects roughly one in five computer users and remains largely unresolved despite decades of ergonomic mouse redesign. All such devices share a fundamental limitation: they still require fine-motor motion to operate.…
arXiv:2511.10027v1 Announce Type: new Abstract: Emergency responders managing hazardous material HAZMAT incidents face critical, time-sensitive decisions, manually navigating extensive chemical guidelines. We investigate whether today’s language models can assist responders by rapidly and reliably understanding critical information, identifying hazards, and…
arXiv:2511.10611v1 Announce Type: cross Abstract: Internet measurement research faces an accessibility crisis: complex analyses require custom integration of multiple specialized tools that demands specialized domain expertise. When network disruptions occur, operators need rapid diagnostic workflows spanning infrastructure mapping, routing analysis,…
arXiv:2511.10037v1 Announce Type: new Abstract: Existing tool-augmented large language models (LLMs) encounter significant challenges when processing complex queries. Current frameworks such as ReAct are prone to local optimization traps due to their reliance on incremental decision-making processes. To address these…
arXiv:2502.10012v2 Announce Type: replace Abstract: Differentiable simulators represent an environment’s dynamics as a differentiable function. Within robotics and autonomous driving, this property is used in Analytic Policy Gradients (APG), which relies on backpropagating through the dynamics to train accurate policies…
arXiv:2511.10038v1 Announce Type: new Abstract: While large language models (LLMs) demonstrate emerging reasoning capabilities, current inference-time expansion methods incur prohibitive computational costs by exhaustive sampling. Through analyzing decoding trajectories, we observe that most next-token predictions align well with the golden…
arXiv:2510.14240v3 Announce Type: replace Abstract: Deep research — producing comprehensive, citation-grounded reports by searching and synthesizing information from hundreds of live web sources — marks an important frontier for agentic systems. To rigorously evaluate this ability, four principles are essential:…
arXiv:2511.10065v1 Announce Type: new Abstract: Radiologists compose diagnostic reports through a structured workflow: they describe visual findings, summarize them into impressions, and carefully refine statements in clinically critical cases. However, most existing medical report generation (MRG) systems treat reports as…
arXiv:2511.08172v2 Announce Type: replace Abstract: Visual grounding is the task of localising image regions from natural language queries and is critical for reasoning capable Graphical User Interface agents. Many existing methods rely on massive, noisy synthetic datasets.This work introduces an…
arXiv:2511.10067v1 Announce Type: new Abstract: Large language models (LLMs) have shown great promise in the medical domain, achieving strong performance on several benchmarks. However, they continue to underperform in real-world medical scenarios, which often demand stronger context-awareness, i.e., the ability…
