AI news archive.
10,657 articles filed under Research, newest first, from the outlets listed on the sources page.
- LessWrongresearchHow We Lose
“It’s unbelievable,” the CEO said. “As in, I literally don’t believe it. Model X can do all of that, but still can’t automate tasks that take our researchers a day?” The engineer nodded carefully. He’d been dreading this…
- arXiv cs.AIresearchCircumventing the Computational Hardness of Computational Arbitrage
arXiv:2610.40831v1 Announce Type: new Abstract: AI model marketplaces host providers with heterogeneous costs and capabilities. These differences create an opportunity for computational arbitrage (Olmedo et al., 2026), i…
- arXiv cs.AIresearchIncongruence-Aware Evaluation of Multimodal Speech Emotion Recognition in Audio Large Language Models
arXiv:2610.40883v1 Announce Type: new Abstract: Voice-interactive large language models process both what a speaker says and how they say it, yet the two channels do not always agree. We ask whether that disagreement deg…
- arXiv cs.AIresearchDiRAFT: Privacy-Aware Financial Transcript Synthesis from Aggregate Discourse Priors
arXiv:2610.40938v1 Announce Type: new Abstract: Using customer conversations to train and evaluate financial language models raises confidentiality concerns because non-public financial facts can remain after direct iden…
- arXiv cs.AIresearchOpening the Box Changes the Cat: LLMs Detect Chain-of-Thought Monitoring - What now?
arXiv:2610.40946v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning allows large language models (LLMs) to generate intermediate reasoning traces in natural language while solving complex tasks. These traces…
- arXiv cs.AIresearchNedimo: An Evidence-Grounded Multilingual Pipeline for AI-Generated Sleep Stories
arXiv:2610.40970v1 Announce Type: new Abstract: Generative audio systems can produce large libraries of personalized bedtime content, but ordinary media objectives (retention, completion, and novelty) are poorly aligned…
- arXiv cs.AIresearchCan Personal Requirements Become Supervision for Planning?
arXiv:2610.40992v1 Announce Type: new Abstract: Managing multiple chronic conditions through diet requires satisfying disease- and medication-specific requirements jointly across meals and days while preserving establish…
- arXiv cs.AIresearchViolet Teaming in Practice: Lessons from a Pilot Expert Workshop on Governing Complex AI Systems
arXiv:2610.41018v1 Announce Type: new Abstract: Violet teaming has been proposed as a method to integrate technical, policy, and societal considerations into the evaluation of emerging technologies. Here, we document a p…
- arXiv cs.AIresearchOptimization Techniques for Solving the Minimum Red--Blue Separating Set Problem with an Application to Human--AI Text Separation
arXiv:2610.41081v1 Announce Type: new Abstract: We study the so-called Minimum Red''Blue Separating Set Problem (MRBSSP) which arises from computational geometry. In particular, we propose a compact Set-Cover ILP formula…
- arXiv cs.AIresearchPayroll Fraud Detection in Synthetic HR/ERP Graphs: An Inductive Comparison of Rules, Path Features, and Graph Neural Networks
arXiv:2610.41085v1 Announce Type: new Abstract: Payroll-fraud screening requires finding hidden employee--payee links while distinguishing suspicious relationships from legitimate ones. We formulate this problem as induc…
- arXiv cs.AIresearchCIRCE Divines LLM Task Complexity from Constraint Structure
arXiv:2610.41089v1 Announce Type: new Abstract: Estimating whether a problem is too complex for a large language model (LLM) before the model attempts it can guide model routing, how to allocate test-time compute, and su…
- arXiv cs.AIresearchQUAL: Quantile Alignment Improves Zero-Shot Time-Series Foundation Models
arXiv:2610.41100v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) provide zero-shot forecasts for unseen series, but their accuracy varies across datasets. Combining several models can reduce this var…
- arXiv cs.AIresearchDifferential rank preservation manifold learning
arXiv:2610.41107v1 Announce Type: new Abstract: Manifold learning methods like t-SNE and UMAP preserve local neighborhoods, but they do not preserve the ranking of the neighbors inside them. Two embeddings can return the…
- arXiv cs.AIresearchCalibration of Large Model Quantization based on HiFloat4 Format
arXiv:2610.41112v1 Announce Type: new Abstract: Quantization of Large Language Models (LLMs) has be- coming increasingly important for reducing the computa- tional costs and resource requirements for practical deploy- me…
- arXiv cs.AIresearchPredicting Human-Gain Curves under Local Proxy Optimization from Repeated Ratings
arXiv:2610.41114v1 Announce Type: new Abstract: Optimizing a proxy objective can improve human-perceived quality, but the resulting gain can vary with optimization strength. Average proxy-human correlation alone does not…
- arXiv cs.AIresearchLifelong Learning of Scheduling Rules with Surrogate-assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling
arXiv:2610.41158v1 Announce Type: new Abstract: Genetic programming (GP) has been widely used to learn scheduling rules for dynamic flexible job shop scheduling (DFJSS). However, trained rules tend to only generalise to…
- arXiv cs.AIresearchFrontierMat: Benchmarking Language Models at the Frontier of Materials R&D
arXiv:2610.41162v1 Announce Type: new Abstract: To accelerate materials discovery, language models must be able to address problems at the research frontier. Yet textbook- and examination-derived benchmarks primarily ass…
- arXiv cs.AIresearchLLM Detoxification via Transition-Aware Reward-Guided Representation Sampling
arXiv:2610.41165v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate toxic content, motivating effective test-time detoxification. Existing representation steering methods often rely on static or coa…
- arXiv cs.AIresearchImplicitHop: Evaluating knowledge integration across context and memory
arXiv:2610.41169v1 Announce Type: new Abstract: The ability to integrate new information and deduce its consequences is central to learning, understanding, and reasoning in large language models (LLMs). Whether informati…
- arXiv cs.AIresearchResearcher-in-the-Loop Evolutionary Discovery of Entanglement-Assisted Quantum Code Families
arXiv:2610.41183v1 Announce Type: new Abstract: LLM-guided program evolution can produce mathematical constructions, but validity, generality, and reproducibility require distinct evidence. We develop a researcher-in-the…
- arXiv cs.AIresearchRTL-Interact: Training EDA-Interactive Models for Multi-Task RTL Design
arXiv:2610.41225v1 Announce Type: new Abstract: Large language models offer a promising route to register-transfer-level (RTL) design, but reliable implementations require checking and revision based on electronic design…
- arXiv cs.AIresearchTRIDENT and SHAKTI: A Framework and Benchmark for Hindi AI-Text Detection
arXiv:2610.41232v1 Announce Type: new Abstract: As Large Language Models (LLMs) become increasingly multilingual, distinguishing human-written from AI-generated text is essential for maintaining information integrity. Ho…
- arXiv cs.AIresearchExperts Exhibit Structured Redundancy: Structure-Preserving Expert Pruning for Mixture-of-Experts Large Language Models
arXiv:2610.41236v1 Announce Type: new Abstract: Sparse MoE mechanism significantly improves the trade-off between model capacity and inference efficiency. However, practical deployment still requires storing all experts,…
- arXiv cs.AIresearchSciGraphSelect: Auditable Scientific Data Selection through Knowledge--Reasoning Graphs
arXiv:2610.41280v1 Announce Type: new Abstract: Scientific data selection is typically driven by relevance or utility scores, providing limited insight into why a document is retained. We introduce SciGraphSelect, a refe…
- arXiv cs.AIresearchSAT-ACT: Learning CDCL Branching from Outcome-Derived Action Preferences
arXiv:2610.41290v1 Announce Type: new Abstract: Learning-based approaches have increasingly been explored for SAT solving, with particular attention to improving branching decisions in conflict-driven clause learning (CD…
- arXiv cs.AIresearchSelf-Improvement with Auxiliary Rewards: Learning from Verified Traces and Evaluating Transfer
arXiv:2610.41296v1 Announce Type: new Abstract: Answer-level rewards cannot distinguish reasoning traces with equally correct outcomes. We study whether auxiliary trajectory preferences improve small-language-model self-…
- arXiv cs.AIresearchSubliminal Reinforcement Learning: traits travel through a judge's scores
arXiv:2610.41301v1 Announce Type: new Abstract: Subliminal learning, the transfer of a model's trait through data with no semantic trace of it, has been shown for students trained on a teacher's text. Post-training relie…
- arXiv cs.AIresearchSERIAL-7: Deriving, Realizing, and Preserving Machine-Verifiable Outputs Across Representations
arXiv:2610.41308v1 Announce Type: new Abstract: Large language models increasingly generate structured outputs consumed by programs and downstream systems, where semantic correctness alone does not guarantee reliable exe…
- arXiv cs.AIresearchDo Transaction Prices Reflect Visual Preference? A Diagnostic Study with Multimodal Language Models
arXiv:2610.41358v1 Announce Type: new Abstract: Existing visual preference evaluation relies on costly human annotations or preference reward models, whereas online marketplace transaction prices are readily available an…
- arXiv cs.AIresearchLEAP: Efficient LLM Inference Scheduling with Generalizable Length Prediction
arXiv:2610.41359v1 Announce Type: new Abstract: Length-aware scheduling reduces request latency in LLM serving by prioritizing shorter requests. However, despite their large model sizes, length predictors can suffer degr…
- arXiv cs.AIresearchRECITE: Revising Eligibility Criteria Incorporating Textual Evidence
arXiv:2610.41368v1 Announce Type: new Abstract: Overly restrictive eligibility criteria contribute to widespread enrollment failure in clinical trials, yet published recommendations for how specific criteria should be br…
- arXiv cs.AIresearchFrom the Zoo to the BULLPEN: Sample-Efficient LLM Profiling via Multi-Channel Model Embeddings
arXiv:2610.41375v1 Announce Type: new Abstract: Choosing among the hundreds of thousands of available large language models (LLMs) requires a thorough understanding of each candidate model's properties. In practice, each…
- arXiv cs.AIresearchOnline Evidence-Containment Prediction over Text Spans under Distinct Queries
arXiv:2610.41384v1 Announce Type: new Abstract: Evidence-grounded NLP systems often verify nested text regions sequentially, so verifying one region constrains others. We formalize this as Online Evidence-Containment Pre…
- arXiv cs.AIresearchscAnyOmics: Foundation-Model Distillation for Any-to-Any Completion of Multi-omics Virtual Cells
arXiv:2610.41399v1 Announce Type: new Abstract: Recent advances in single-cell technologies have enabled the profiling of multiple molecular modalities, including transcriptomics, proteomics, and chromatin accessibility,…
- arXiv cs.AIresearchCryoAtlas: A Large Curated Dataset and Unified Benchmark for Cryo-EM Atomic Model Building
arXiv:2610.41411v1 Announce Type: new Abstract: Deep learning has accelerated automated atomic model building from cryo-EM maps, yet progress remains limited by the lack of large, high-quality datasets and standardized e…
- arXiv cs.AIresearchMulti-Test Nation Bias Benchmarking of LLMs with Explicit Unbiased Baselines
arXiv:2610.41486v1 Announce Type: new Abstract: While prior work has highlighted that systematic nation-level bias in large language models (LLMs) can pose operational risks for international relations (IR) applications,…
- arXiv cs.AIresearchSpecification-Guided Generation for Large Language Models
arXiv:2610.41511v1 Announce Type: new Abstract: Large language models (LLMs) can generate structured outputs, but existing constrained-decoding methods mainly enforce syntax and cannot directly enforce satisfaction of a…
- arXiv cs.AIresearchConnectivity-Aware Client Selection in Decentralized Federated Learning
arXiv:2610.41570v1 Announce Type: new Abstract: Decentralized federated learning (DFL) has emerged as a scalable alternative to centralized federated learning, removing the single point of failure and communication bottl…
- arXiv cs.AIresearchPatch-Based Deep Kernel Learning for Data Assimilation and Bias Correction with Extremely Sparse Observations
arXiv:2610.41596v1 Announce Type: new Abstract: Data Assimilation (DA) reconstructs the state of a spatio-temporal system by combining sensor observations with the output of a numerical model. Since model states are high…
- arXiv cs.AIresearchWhat Should LLMs Forget: Reinforcement Unlearning of Knowledge Associations
arXiv:2610.41616v1 Announce Type: new Abstract: Large language models (LLMs) acquire extensive factual knowledge during pre-training, which may include sensitive, private, or copyrighted information, motivating the devel…
- arXiv cs.AIresearchRisk-Sensitive Mission Planning for Multi-Target On-Orbit Inspection via Distributional Reinforcement Learning
arXiv:2610.41647v1 Announce Type: new Abstract: Multi-target on-orbit servicing missions require planning tools that can adapt to evolving operational conditions while accounting for the outcome variability inherent to s…
- arXiv cs.AIresearchBreaking Information Islands in Sparse Tuning via Small-World Connectivity
arXiv:2610.41665v1 Announce Type: new Abstract: Sparse tuning is widely used to adapt large language models due to its parameter efficiency. However, its effectiveness depends not only on the number of trainable paramete…
- arXiv cs.AIresearchRadial Kernel Attention for Long-Range Modeling in Polymer Machine Learning Force Fields
arXiv:2610.41675v1 Announce Type: new Abstract: We introduce Radial Kernel Attention (RKA) for long-range modeling in polymer machine learning force fields. Local neighbor graphs constrain communication across polymer ch…
- arXiv cs.AIresearchAdvancing Clinical Trial Outcome Prediction with Domain-Specific Large Language Models
arXiv:2610.41710v1 Announce Type: new Abstract: Clinical trial failures are a major barrier to efficient drug development, incurring substantial costs and delaying patient access to effective therapies. Structured approa…
- arXiv cs.AIresearchMultimodal In-Context Learning with Explicit Rule Induction
arXiv:2610.41754v1 Announce Type: new Abstract: A central challenge in multimodal in-context learning (MICL) arises from tasks that are ill-defined without context and require uncovering the underlying rules from demonst…
- arXiv cs.AIresearchWhose Values, Which Contexts, and What Signals? Grounding Cultural Value Alignment with Re3Culture
arXiv:2610.41793v1 Announce Type: new Abstract: Cultural value alignment requires not only model optimization but also a well-specified target grounded in real-human evidence. Yet how such targets should be grounded in h…
- arXiv cs.AIresearchRECAST: REconstruction of Chain-of-Thought via Auditable Structured Traces
arXiv:2610.41813v1 Announce Type: new Abstract: Large closed-source reasoning models expose only their final answers. The intermediate reasoning that produces those answers is hidden behind API surfaces, tool-call polici…
- arXiv cs.AIresearchReuScope: Auditing Data Reuse and Evaluation Sensitivity in Capsule Vision 2024
arXiv:2610.41835v1 Announce Type: new Abstract: We develop ReuScope, a protocol for auditing data reuse and evaluation sensitivity, using Capsule Vision 2024 as a case study. It combines measurements of data relationship…
- arXiv cs.AIresearchDynamical Memory Transformer: Selective Recurrent Memories with Constant Cost Attention
arXiv:2610.41850v1 Announce Type: new Abstract: Transformers retain an explicit history of the sequence, allowing attention to directly retrieve past representations. However, the size of the KV-Cache and the cost of a n…
- arXiv cs.AIresearchFuzzy selective state model for forecasting the dynamics of consumer preferences
arXiv:2610.41879v1 Announce Type: new Abstract: We consider forecasting the dynamics of consumer preferences of retail chain customers. A customer's preference is described by a triangular fuzzy number. The evolution of…