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Artificial Intelligence
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The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 210
Reliable Knowledge Acquisition for Continual Learning Agents
As agents powered by foundation models move into open-ended environments, continual learning from experience becomes essential.The Delegation Dilemma: Economies of Scale, Accountability, and Polycentric Governance
Many collective-action systems are neither fully decentralized nor fully centralized: agents voluntarily organize into institutions that share organizational costs and delegate decisions to…Harmful Partial Interventions and Benign Leakage in Concept-based Models
Artificial intelligence systems deployed in high-risk settings increasingly require models that support meaningful human oversight.DeciCAD: Harness-Grounded Learning of Action Policies for CAD Agents
Large Language Model agents operate through closed-loop action policies whose decision space is defined by an agent harness.From Research Goals to Scientific Closure: Evaluating Agents Through Evidence-Supported Physics Research
Can AI agents organize scientific investigations that lead to well-supported conclusions?CF-AVSS: A Coarse-to-Fine Audio-Visual Speech Separation Framework with Target-Speaker Refinement and Post-Fusion for Real-World AVSE Challenge
Audio-visual speech enhancement (AVSE) leverages visual cues to recover target speech from mixtures corrupted by reverberation, noise, and overlapping speakers.DINO-FIL: Multi-Layer Transformer Fusion for Generative Inpainting Forgery Localization
We propose DINO-FIL, a transformer-based framework for pixel-level localization of generative image forgeries.In the Guise of Correction: How Framing and Cultural Adaptation Erode LLM Safety on Real-World Criminal Cases
Existing safety benchmarks rely largely on synthetic prompts with loosely grounded taxonomies and offer little focused analysis of severe crime categories.RSIFlow: Adaptive Self-Improvement Workflows with an Evolving Meta-Agent
Large language model (LLM) agents have demonstrated strong capabilities in complex tasks, including code generation, tool use, and multi-hop question answering.Cross-Embodiment Causal Transfer from Human Videos to Robot Manipulation
Scaling robot manipulation models requires large amounts of interaction data, yet collecting diverse real-robot experience remains costly.Co2In: a Bi-level Memory Incremental Learning Framework with Knowledge Encoding, Consolidation, and Integration
Incremental learning (IL) aims to continually acquire new knowledge (plasticity) while retaining previously learned information (stability).CIM-Embed: Learning Instruction-Conditioned Multimodal Embeddings for Clustering
Multimodal objects can require different partitions under different instructions, as when products in an e-commerce catalog are grouped by color, material, or both.RoleQ: Role-Aligned Scales for Converting Language Models to Ternary
Weight quantization below four bits shrinks memory and bandwidth at a perplexity that looks acceptable, but often at the cost of factual knowledge and task accuracy.Provably Efficient Risk-Sensitive Offline Reinforcement Learning via Optimized Certainty Equivalents
Risk-sensitive reinforcement learning (RL) addresses decision-making under uncertainty and adverse outcomes.Anvil: Scaling Embodied Spatial Intelligence through Knowledge Recirculation
Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this knowledge in action-relevant forms.In-Context Learning Before Specialisation: Theory of Learning in a Solvable Topic Model
Sequence models can generalise in fundamentally distinct ways: extrapolating structures seen in training, or using their prompt to adapt to novel tasks.CoWorld Reasoner: Agentic Multimodal Reasoning with the Evolving Video World Model-Driven Harness
As Vision-Language Models (VLMs) advance, they are increasingly expected to perform spatiotemporal reasoning over motion, actions, and view changes beyond what the input images show.Learning Rewards in Strategic Games
Understanding the objectives that drive agents' behavior is crucial in strategic environments, where multiple agents interact and adapt to one another.CodeHealth Predicts the Token Cost of Agentic Code Review: A Pre-Registered Study of 465 Agent-Authored Pull Requests
Organizations increasingly delegate code review to multi-agent large language model (LLM) pipelines billed per token.BridgeAfford: Bridging Query-Target Gap for Generalizable 3D Affordance Grounding
Language-guided 3D affordance grounding aims to localize functional regions on 3D objects according to interaction intents.