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Artificial Intelligence
The newest papers in Artificial Intelligence that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
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 219
From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation Agents
Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agent needs to learn.AgentSafeEvo: Adversarial Co-Evolution for LLM Agent Safety
Large language model (LLM) agents accomplish complex tasks through multi-turn interactions with external tools.Beyond the Trial-and-Error Loop: Hybrid Projection and Automated Tuning for Distributed Training
Configuring distributed LLM training across hundreds of GPUs requires jointly optimizing tensor, pipeline, expert, context, and data parallelism alongside micro-batch size, recomputation, sharding…VideoHarness-SRSI: Structured Recursive Self-Improvement for Video Understanding Harness
LLM system capabilities depend not only on model parameters but also on the executable harnesses that organize information acquisition, tool use, reasoning, and memory.Evaluating Agentic Capabilities Before Post-Training: An End-to-End Approach
Agentic capabilities are increasingly important for modern LLMs, yet remain difficult to evaluate during pretraining.How Do LLMs Understand Legal Philosophy? Diagnosing Legal-Philosophical Reasoning in LLMs
Legal reasoning is a fundamental capability for large language models (LLMs) to complete legal AI tasks such as legal judgment prediction.Recognition Is Not Grounding: Benchmarking Multilingual Financial Evidence Extraction
Comparing financial disclosures across languages requires identifying shared accounting concepts and recovering all numerical facts that express them.EvoProbe: Evaluation-Driven Benchmark Evolution for LLM Agents
Static benchmarks for large language model (LLM) agents face saturation and data contamination risks, motivating continual updates to evaluation tasks.Integrating Simulation and Chain-of-thought Reasoning in Multimodal-Language Models For Physical Reasoning
Multimodal language models often need to reason about the physical dynamics of the world in order to answer questions appropriately.xLightGCN: Explainable Graph Neural Network Based Recommendation Systems with Most Influential Peers
Recommendation systems, systems that predict a user's preference for items in order to curate that user's feed, are a ubiquitous and central feature in online social networks.Are You Reading the Right Thing? Rethinking Internal Signals for Prompt-Injection Detection
Several recent studies propose detecting prompt injections from a language model's internal state.AdCoEvo: A Co-Evolving Multi-Agent Advertising Delivery System
Digital advertising is an important means for platforms to reach potential users and drive business growth.MIPS: Mitigating Mode Collapse in Reinforcement Learning for Large Outcome Spaces
Expected-reward maximization in reinforcement learning concentrates probability mass on a few outcomes, even in tasks that require many distinct, high-quality solutions, a failure known as mode…PFedMA: Who Should Join Next as Federated Multi-Agent Orchestration Evolves?
Federated Multi-Agent Systems (FedMAS) offer a promising paradigm for collaborative reasoning among LLM-based agents while keeping raw client data decentralized.MemCode: Discrete Semantic Representations for Long-Term Agent Memory
Long-term memory remains a fundamental bottleneck for large language model (LLM) agents across sessions.When Agent Memory Needs to Compute: Evidence Access and Executable Aggregation
Questions about an agent's history often require aggregating events, which retrieval alone does not resolve.IMU-Bench: Benchmarking Wrist IMU Representations Across Kinematic, Semantic and Clinical Tasks
Wrist-worn inertial measurement units (IMUs) provide a common sensing modality for tasks ranging from activity and gesture recognition to pose estimation, inertial odometry and clinical motor…Robust Real-Time Monocular Human Pose Estimation with Insole-Based Sensor Fusion
Real-time monocular human pose estimation is an important sensing component for human-centered intelligent systems.Structure-Preserving Document-Level Data Augmentation via Discourse Parsing
Data augmentation (DA) plays a vital role in improving model performance in low-resource or limited-supervision scenarios within Natural Language Processing (NLP).Structure Before Intelligence: Gating What Agentic Scientific Workflows Release
An agentic scientific workflow can run to completion and still release wrong results: a silent numerical error, a stale input, or a defect in a shared upstream step can contaminate several outputs…