Search: “agents”

arXiv:2605.15128v1 Announce Type: cross Abstract: Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later r

arXiv:2605.14389v1 Announce Type: new Abstract: Time series forecasting is not just numerical extrapolation, but often requires reasoning with unstructured contextual data such as news or events. Whil

arXiv:2605.14002v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) embedded in agentic frameworks have transformed information retrieval from static, long context question answering into op

arXiv:2605.14700v1 Announce Type: new Abstract: Generating robot simulation environments remains a major bottleneck in simulation-based robot learning. Constructing a training-ready MuJoCo scene typic

arXiv:2605.12856v1 Announce Type: new Abstract: The emergence of multi-agent systems introduces novel moderation challenges that extend beyond content filtering. Agents with {em malicious intent} may

arXiv:2605.13345v1 Announce Type: new Abstract: Emergency departments (ED) face challenges in patient care and resource management. We propose to explore optimization strategies in a realistic and fle

arXiv:2507.15867v2 Announce Type: replace-cross Abstract: Rare diseases affect 1 in 10 Americans yet remain systematically underdocumented in clinical records. ICD-based systems cannot capture their b

arXiv:2605.12745v1 Announce Type: cross Abstract: Discrepancies between an agent's actual knowledge and what a person thinks the agent knows can hinder interactions. If an agent could detect such disc

arXiv:2605.11951v1 Announce Type: new Abstract: Although robotic manipulation has made significant progress, reliable execution remains challenging because task failures are inevitable in dynamic and

arXiv:2605.12004v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) for Large Language Models (LLMs) critically depends on the exploration capability of the base policy, as training si

arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread

arXiv:2605.09951v1 Announce Type: new Abstract: ML models in healthcare are typically evaluated using curated real-world EHR data. A key limitation of such evaluations is that they may fail to assess

arXiv:2507.15518v5 Announce Type: replace Abstract: Creating an immersive and interactive theatrical experience is a long-term goal in the field of interactive narrative. The emergence of large langua

arXiv:2605.08978v1 Announce Type: new Abstract: Recent advancements in agentic test-time scaling allow models to gather environmental feedback before committing to final actions. A key limitation of e

arXiv:2605.09822v1 Announce Type: cross Abstract: We define Oracle Poisoning, an attack class in which an adversary corrupts a structured knowledge graph that AI agents query at runtime via tool-use p

arXiv:2604.01527v3 Announce Type: replace-cross Abstract: Production deployment of AI coding agents requires fast, reproducible evaluation signals. Existing industrial practices trade off speed and fi

arXiv:2605.10057v1 Announce Type: new Abstract: Compositional spatiotemporal reasoning often requires a system to invoke multiple heterogeneous specialists, such as geometric, temporal, topological, a

arXiv:2601.22638v2 Announce Type: replace-cross Abstract: The exponential growth of machine learning submissions has strained the traditional peer review process, resulting in slow feedback loops for

arXiv:2605.10698v1 Announce Type: cross Abstract: Multi-agent systems (MAS) assume that collaborating inherently improves Large Language Model (LLM) reasoning. We challenge this by demonstrating that

arXiv:2605.09330v1 Announce Type: cross Abstract: Agentic memory enables LLMs to persist information beyond a single context window and reuse it in later decisions, but it also introduces a new vulner

arXiv:2602.04672v3 Announce Type: replace Abstract: Reconstructing dynamic hand-object interactions from monocular videos is critical for dexterous manipulation data collection and creating realistic

arXiv:2512.03476v2 Announce Type: replace-cross Abstract: Bridging the gap between theoretical conceptualization and computational implementation is a major bottleneck in Scientific Computing (SciC) a

arXiv:2605.07457v1 Announce Type: new Abstract: Recent text-guided image editing (TIE) models have made remarkable progress, yet edited images still frequently suffer from fine-grained issues such as

arXiv:2605.07510v1 Announce Type: cross Abstract: Existing benchmarks for multimodal agentic search evaluate multimodal search and visual browsing, but visual evidence is either confined to the input

arXiv:2605.06864v1 Announce Type: new Abstract: We study multi-objective multi-agent multi-armed bandits (MO-MA-MAB) under stochastic rewards, where agents observe heterogeneous reward vectors and com

arXiv:2605.07202v1 Announce Type: new Abstract: Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limi

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

arXiv:2605.04304v1 Announce Type: cross Abstract: Advanced chart question answering requires both precise perception of small visual elements and multi-step reasoning across several subplots. While ex

arXiv:2602.19837v3 Announce Type: replace-cross Abstract: Humans are highly effective at utilizing prior knowledge to adapt to novel tasks, a capability that standard machine learning models struggle

arXiv:2605.04012v1 Announce Type: new Abstract: Language models excel at diagnostic assessments on currated medical case-studies and vignettes, performing on par with, or better than, clinical profess

arXiv:2410.17517v5 Announce Type: replace-cross Abstract: Decision-making is an essential attribute of any intelligent agent or group. Natural systems are known to converge to effective strategies thr

arXiv:2605.02366v1 Announce Type: new Abstract: Research funding discovery remains fundamentally fragmented: researchers navigate disparate agency portals (e.g., in the United States, NSF, NIH, DARPA,

arXiv:2605.02741v1 Announce Type: cross Abstract: The promise of Large Language Models in automated software engineering is often measured by functional correctness, overlooking the critical issue of

arXiv:2603.00822v2 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents increasingly execute complex, autonomous software engineering tasks, developers rely on natural language

arXiv:2605.03310v1 Announce Type: cross Abstract: Multi-agent LLM systems fail in production at rates between 41% and 87%, mostly due to coordination defects rather than base-model capability. Existin

arXiv:2605.02503v1 Announce Type: new Abstract: Evaluating autonomous data analysis agents requires testing their ability to perform exploratory analysis in underexplored data environments. However, m

arXiv:2604.00187v2 Announce Type: replace-cross Abstract: Explainable Artificial Intelligence (XAI) is critical for ensuring trust and accountability, yet its development remains predominantly visual.

arXiv:2605.02491v1 Announce Type: cross Abstract: Modern searches for physics beyond the Standard Model produce rapidly expanding literature containing heterogeneous information, including textual ana

arXiv:2605.02092v1 Announce Type: new Abstract: The automation of scientific research workflows has emerged as a transformative frontier in artificial intelligence, yet existing autonomous research ag

arXiv:2605.02728v1 Announce Type: new Abstract: This paper presents ORPilot, an open-source agentic AI system that translates real-world business problems into solver-ready optimization models. Unlike

arXiv:2605.03788v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly explored as high-level reasoning engines for cyber-physical systems, yet their application to real-time

arXiv:2602.03548v3 Announce Type: replace Abstract: Large Language Models have demonstrated remarkable capabilities in open-domain dialogues. However, current methods exhibit suboptimal performance in

arXiv:2605.01750v1 Announce Type: cross Abstract: Grounding is the collaborative process of establishing mutual belief sufficient for the current communicative purpose. While static grounding maps lan

arXiv:2605.00276v1 Announce Type: new Abstract: Trip planning for intelligent vehicles increasingly requires selecting optimal routes rather than merely producing feasible itineraries, as interacting

arXiv:2605.00073v1 Announce Type: new Abstract: Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security audi

arXiv:2601.12024v2 Announce Type: replace-cross Abstract: Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommenda