Search: “persistence”

arXiv:2610.17434v1 Announce Type: new Abstract: Recent advances in video world models have enabled plausible interactive environments, yet long-horizon generation places a fundamental demand on visual

arXiv:2610.12118v1 Announce Type: new Abstract: Automated methods have been proposed to overcome the limitations of human verbal deception detection, but evidence remains fragmented across disciplines

arXiv:2610.05207v1 Announce Type: new Abstract: Feed-forward 3D models provide strong multi-view geometric priors, while on- line simultaneous localization and mapping (SLAM) relies mainly on local me

arXiv:2610.02162v1 Announce Type: new Abstract: How can a world model continuously observe regions beyond the actor's current view? Video world models simulate how an environment evolves from an agent

arXiv:2609.35402v1 Announce Type: new Abstract: When pricing agents meet repeatedly on a platform, the platform decides who faces whom. We ask whether that choice moves the prices the agents learn, an

arXiv:2609.26147v1 Announce Type: new Abstract: Modern LLMs are deployed as families of post-trained variants (base, instruct, chat, code) derived from a shared set of pre-trained weights. We present

arXiv:2609.22854v1 Announce Type: cross Abstract: Vision-language-action models often predict actions from only the current observation, which can leave tasks involving object occlusion or visually id

arXiv:2609.22195v1 Announce Type: new Abstract: Large language models can convincingly adopt personas, recall past dialogues, and weave rich autobiographies. Yet this conversational eloquence conceals

arXiv:2609.21713v1 Announce Type: cross Abstract: Edge AI accelerators are increasingly deployed in safety-critical environments, where model outputs may control physical actuators, make access-contro

arXiv:2609.17590v1 Announce Type: cross Abstract: Evolutionary Ensemble Search (EES) constructs machine-learning procedures through expert-guided program evolution. A role-specialized council turns ta

arXiv:2603.25685v2 Announce Type: replace-cross Abstract: Action-conditioned robot world models generate future video frames of the manipulated scene given a robot action sequence, offering a promisin

arXiv:2608.31167v1 Announce Type: cross Abstract: Bridging model-based control and learned policies in long-horizon manipulation has harbored a silent disagreement: control executes specified objectiv

arXiv:2608.24952v1 Announce Type: new Abstract: Systematic dialectal performance gaps in language models (LMs) are well documented, but the source of these disparities within the modern language model

arXiv:2608.10875v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained re

arXiv:2608.08570v1 Announce Type: new Abstract: Rejection sampling fine-tuning (RFT) is widely used to train code agents by generating trajectories on verifiable software engineering tasks, retaining

arXiv:2607.29008v1 Announce Type: cross Abstract: Modern opaque AI models prize performance over interpretability, which makes testing difficult. However, formal statistical tests conducted on a model

arXiv:2607.22917v1 Announce Type: new Abstract: Large Language Model (LLM) agents have significantly improved coding and programming workflows. Claude Code, in particular, is one of the most powerful

arXiv:2607.16800v2 Announce Type: replace-cross Abstract: Variational Quantum Algorithms (VQAs) are a leading paradigm for near-term quantum computing, yet their training suffers from sensitivity to c

arXiv:2601.14271v2 Announce Type: replace Abstract: Shared accountability records are often used by parties who may never agree about causation, responsibility, or normative interpretation. For such r

arXiv:2606.26502v1 Announce Type: new Abstract: Large reasoning models (LRMs) take longer on harder problems, just as humans do. This surface similarity hides an opposite pattern within items. When an

arXiv:2606.23884v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used for mental health-related conversations, yet safety safeguards remain inadequate an

arXiv:2606.02750v1 Announce Type: new Abstract: Representations extracted from large language models (LLMs) play an important role in many downstream applications. However, the structure of these repr

arXiv:2602.17063v2 Announce Type: replace-cross Abstract: Sub-bit model compression targets storage below one bit per weight; as magnitudes are aggressively compressed, the sign bit becomes a fixed-co

arXiv:2605.24922v1 Announce Type: new Abstract: We present MuJoCoUni, a downstream MuJoCo distribution for online robot learning and batched physics evaluation. Alongside the open-loop batched traject

arXiv:2605.17596v1 Announce Type: new Abstract: We present NeuSymMS, an adaptive memory system that enables large language model (LLM) agents to learn, remember, and reason about users across sessions

arXiv:2604.08230v1 Announce Type: new Abstract: Object detection models trained on a source domain often exhibit significant performance degradation when deployed in unseen target domains, due to vari

arXiv:2606.04425v1 Announce Type: cross Abstract: Modern agentic systems transform LLMs from session-bounded assistants into stateful systems that persist and evolve shared world state across sessions

arXiv:2603.01209v3 Announce Type: replace Abstract: In CodeAct, language-model agents write Python that calls tools and use execution feedback to choose actions. Persistent runtimes preserve Python va

arXiv:2609.08886v1 Announce Type: new Abstract: Language-guided robots need persistent scene memories to follow instructions, revisit objects, and resolve references to objects encountered over time.

arXiv:2608.21479v1 Announce Type: cross Abstract: Magnitude homology is graded by length and knows nothing of persistence. Its persistent refinement knows nothing of where its bars begin and end. We s

arXiv:2608.17597v1 Announce Type: cross Abstract: Large language models are increasingly deployed through agent harnesses that manage tools, extensions, persistent state, permissions, and external act

arXiv:2607.27834v1 Announce Type: cross Abstract: Persistent memory lets long-running large language model agents reuse information across sessions and tasks. Yet errors in writable memory can persist

arXiv:2402.15058v3 Announce Type: replace-cross Abstract: We combine standard persistent homology with image persistent homology to define a novel way of characterizing shapes and interactions between

arXiv:2610.02150v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on persistent external sources to solve sequences of knowledge-intensive tasks. Existing methods i

arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community bound

arXiv:2609.25053v1 Announce Type: new Abstract: Can one language model hand its live memory to another without the receiver rereading the context? We demonstrate useful persistent hybrid-state transfe

arXiv:2609.21400v1 Announce Type: new Abstract: Open-vocabulary 3D scene mapping aims to build a persistent representation of the objects in an environment. Existing systems typically rely on engineer

arXiv:2609.05446v1 Announce Type: new Abstract: We introduce AutoFyn, an agent harness inspired by the Expert Iteration algorithm, adapting a frozen model across many rounds by updating persistent sta

arXiv:2609.10540v1 Announce Type: new Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent wo

arXiv:2607.14252v2 Announce Type: replace-cross Abstract: Embodied agents accumulate experience over time. We study how accumulated experience can be formed into persistent memory for future reasoning

arXiv:2608.10502v1 Announce Type: new Abstract: Persistent memory lets language-model agents reuse information across sessions, but it also makes errors durable: a poisoned, stale, or misattributed re

arXiv:2607.29400v1 Announce Type: new Abstract: A routing decision can be revised at the next transaction, but a latched source exclusion persists across later decisions. We ask what evidence should a

arXiv:2607.27539v1 Announce Type: cross Abstract: Exact deletion from persistent language-model memory depends on how that memory represents a record. Addressable influence can be removed by algebraic

arXiv:2607.11149v3 Announce Type: replace Abstract: LLM agent benchmarks measure task completion, reliability, and inference cost, but not the persistent data an agent run leaves on disk, including lo

arXiv:2605.06731v1 Announce Type: cross Abstract: Personalized LLM agents maintain persistent cross-session state to support long-horizon collaboration. Yet, this persistence introduces a subtle but c

arXiv:2604.23338v1 Announce Type: cross Abstract: Agentic AI systems face security challenges that stateless large language models do not. They plan across extended horizons, maintain persistent memor