CompanyAnthropic8 recent entries30 Sept 2026Accessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding AccessarXiv:2609.36129v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expa→1 Oct 2026Self-Spec Verifiable Code GenerationarXiv:2609.39568v1 Announce Type: cross Abstract: Large language models (LLMs) may generate unreliable code on corner cases missed by testing, while formal verification can provide machine-checkable g
CompanyOpenAI8 recent entries25 Sept 2026Control the Harness, Control the Cost: Routing and Governing AI Coding Agents in the EnterprisearXiv:2609.28919v1 Announce Type: new Abstract: Harnesses, the products that run AI coding agents, are multiplying, and enterprises are rolling them out to their employees: what started as pilots with→30 Sept 2026Accessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding AccessarXiv:2609.36129v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expa→1 Oct 2026Cascadia: A Control-Plane-Free Alternative to Hyperconverged AI InfrastructurearXiv:2609.38697v1 Announce Type: cross Abstract: We present Cascadia, a system for serving large language models on fleets of commodity Intel AIPCs using their CPU, integrated-GPU, and NPU resources.→5 Oct 2026Unmasking Propaganda: A Comparative Analysis of Masked and Causal Language ModelsarXiv:2610.03077v1 Announce Type: new Abstract: Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. Ho→5 Oct 2026Mitigating Private Data Leakage in LLMs with WhiteoutarXiv:2610.02418v1 Announce Type: cross Abstract: Modern large language models (LLMs) are trained on massive, largely unfiltered datasets, including content scraped from nearly every accessible websit→6 Oct 2026Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based PromptsarXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr→7 Oct 2026JEV versus LLMs: Accuracy, Cost and Calibration on Seven Political Science ReplicationsarXiv:2610.06625v2 Announce Type: replace Abstract: Large language models (LLMs) annotate and scale political text or constructs by generating text tokens. A new class of models, which TypeSafe market→9 Oct 2026Writing for the Reviewer: Defensive Writing in GPT ModelsarXiv:2610.11355v1 Announce Type: new Abstract: Researchers increasingly use ChatGPT to revise their papers, and recent GPT versions often narrow or even retract the authors' claims. We call such chan
CompanyGoogle8 recent entries29 Sept 2026See, Measure, and Reason: Learning Visually Grounded Reasoning in PathologyarXiv:2609.34277v1 Announce Type: new Abstract: Pathological assessment relies on recognizing fine-grained visual details in histological images. Vision-language models (VLMs) increasingly support pat→30 Sept 2026Larry Caused the Car to Stop, But the Model Didn't Notice: Transformer Blindness to the M-HeuristicarXiv:2609.37497v1 Announce Type: new Abstract: Modern transformer models excel at capturing semantic relationships through sentence embeddings, yet their ability to perform pragmatic reasoning remain→1 Oct 2026Cogentic: Multi-Agent Orchestration for Automated Proof DiscoveryarXiv:2609.40324v1 Announce Type: new Abstract: We present Cogentic, a multi-agent harness for automated proof discovery on open research problems. While frontier language models can generate strong m→6 Oct 2026One Figure, Every Canvas: Editable Flowchart Relayout via Agentic PipelinearXiv:2610.06852v1 Announce Type: new Abstract: Pipeline figures in ML papers must be repurposed across many canvases, including paper columns, 16:9 slides, portrait posters, 1:1 social teasers, 9:16 →6 Oct 2026Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based PromptsarXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr→7 Oct 2026Who Wrote It Is Not Enough: Detecting Who Contributed the InsightarXiv:2610.07365v1 Announce Type: new Abstract: As LLMs increasingly assist scientific writing and peer review, detecting who wrote the text is no longer sufficient: we need to determine who contribut→7 Oct 2026Image Bitstream Fine-grained Understanding for Privacy-Friendly AIoTarXiv:2610.08414v1 Announce Type: new Abstract: Image Bitstream Fine-grained Understanding (IBFU) aims to directly perform fine-grained classification and semantic description generation from encoded →12 Oct 2026MathVis: Can AI Reason through Drawing? A Benchmark for Mathematical Figure GenerationarXiv:2610.12954v1 Announce Type: new Abstract: This paper introduces MathVis, a benchmark designed to evaluate LLMs' ability to visualize frontier mathematical problems and perform diagram-assisted r
CompanyMeta8 recent entries7 Oct 2026Thin Evidence, Thick Priors: How Language Models Substitute Identity for Missing Financial FactsarXiv:2610.07798v1 Announce Type: new Abstract: People increasingly ask large language models what to do with their money, yet seldom describe their finances in full. This paper asks what a model does→7 Oct 2026SSR: Sparse Segment Reduction for Ternary GEMM AccelerationarXiv:2610.08403v1 Announce Type: new Abstract: Large Language Models (LLMs) require substantial computational resources, limiting their deployment on resource-constrained hardware. Ternary LLMs mitig→7 Oct 2026CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML DatasetsarXiv:2610.07132v1 Announce Type: cross Abstract: Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful read→8 Oct 2026Zero-shot Video Moment Retrieval via Off-the-shelf Multimodal Large Language ModelsarXiv:2501.07972v2 Announce Type: replace-cross Abstract: The target of video moment retrieval (VMR) is predicting temporal spans within a video that semantically match a given linguistic query. Exist→9 Oct 2026MetaOPD: Meta-Learned Token Weighting for On-Policy DistillationarXiv:2610.11989v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own generated responses using token-level teacher supervision. However, uniform weighting overlooks→12 Oct 2026Hyper Algorithm Design Agent: Evolving Learnable Optimizer from ZeroarXiv:2609.35328v2 Announce Type: replace Abstract: Meta-Black-Box Optimization (MetaBBO) is one of the highlights in the recent AI for Optimization trend. This paradigm's bi-level workflow leverages →12 Oct 2026CORE-Seg: Reasoning-Driven Segmentation for Complex Lesions via Reinforcement LearningarXiv:2603.05911v2 Announce Type: replace-cross Abstract: Medical image segmentation is undergoing a paradigm shift from conventional visual pattern matching to cognitive reasoning analysis. Although →12 Oct 2026Byzantine-Resilient Federated Large Language Model via Hypergraph Message PassingarXiv:2610.12711v1 Announce Type: new Abstract: Federated Large Language Models (FedLLMs) are promising to deliver privacy-preserving, collaborative intelligence. The decentralized training process is
CompanyMistral8 recent entries17 Sept 2026Reading Between the Lines: Can LLMs Discover the Question Behind the Text?arXiv:2609.19070v1 Announce Type: new Abstract: This paper introduces ``question archaeology'', a specific evaluation task focused on inferring the single, authentic 'genesis question' that motivated →17 Sept 2026A Zeroth-Order Paradigm for LLM Preference AlignmentarXiv:2609.19144v1 Announce Type: cross Abstract: Direct preference alignment methods are widely used to align large language models (LLMs) with human preferences because of their computational and me→23 Sept 2026Same Quantity, Different Answer: Numerical Representation Invariance in Language ModelsarXiv:2609.25009v1 Announce Type: new Abstract: Numerically equivalent word problems should yield the same canonical answer whether a quantity is written as a decimal, fraction, percentage, number wor→28 Sept 2026From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMsarXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-sou→28 Sept 2026Energy Efficiency of Locally Deployed LLMs: A Preliminary Quantitative GPU Power Benchmark on Consumer HardwarearXiv:2608.00008v2 Announce Type: replace Abstract: The local deployment of large language models (LLMs) is gaining traction due to privacy concerns and the desire for on-premise inference. However, t→1 Oct 2026DataFlex: A Unified Framework for Data-Centric Dynamic Training of Large Language ModelsarXiv:2603.26164v2 Announce Type: replace-cross Abstract: Data-centric training has emerged as a promising direction for improving large language models (LLMs) by optimizing not only model parameters →2 Oct 2026AVSD-Scenes: A Dataset for Audio-Visual Description of Urban ScenesarXiv:2610.01861v1 Announce Type: new Abstract: Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory a→5 Oct 2026Unmasking Propaganda: A Comparative Analysis of Masked and Causal Language ModelsarXiv:2610.03077v1 Announce Type: new Abstract: Propaganda detection is an essential task in natural language processing (NLP), particularly in the context of manipulative political communications. Ho
CompanyxAI8 recent entries28 Sept 2026A Synthetic Ground-Truth Framework for the Evaluation of Explainable AI MethodsarXiv:2609.30397v1 Announce Type: new Abstract: Evaluating explainable Artificial Intelligence (XAI) methods is a challenging task due to the lack of reliable evaluation procedures and, in particular,→29 Sept 2026Self-eXplainable AI for Medical Image Analysis: A Survey and New OutlooksarXiv:2410.02331v3 Announce Type: replace Abstract: The increasing demand for transparent and reliable models, particularly in high-stakes decision-making areas such as medical image analysis, has led→29 Sept 2026Evaluating Single and Multi-Omics Based Explainable Artificial Intelligence (MOXAI) for Molecular Subclass Classification of Adult-Type Diffuse GliomasarXiv:2609.32190v1 Announce Type: new Abstract: DNA methylation (DNAM) profiling has emerged as a powerful diagnostic tool for classifying brain and solid tumors. However, existing computational model→6 Oct 2026TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being FeedbackarXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf→6 Oct 2026Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based PromptsarXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr→7 Oct 2026FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow MatchingarXiv:2610.08537v1 Announce Type: cross Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would →12 Oct 2026Faithfulness Without Anchors: A Position Paper on the Structural Misalignments of Explainable AI Faithfulness Metrics for Feature ImportancearXiv:2610.12493v1 Announce Type: new Abstract: Explainable Artificial Intelligence (XAI) tools have often been presented as methods to increase trust in machine learning models by making aspects of t→12 Oct 2026Controlled-Minimax: Stabilizing Adversarial Optimization via Control TheoryarXiv:2610.12915v1 Announce Type: new Abstract: Minimax optimization is fundamental to adversarial learning yet suffers from severe stability challenges, often manifesting as persistent limit cycles o
CompanyDeepSeek8 recent entries1 Oct 2026Evaluating Whether LLMs Can Reliably Connect the DOTs?arXiv:2609.38406v1 Announce Type: new Abstract: Access to real-world information is often noisy and fragmented. Constructing a coherent narrative from such fragments requires models to reconstruct mis→2 Oct 2026MoRA: MoE Pruning via Router Bias Learning and Expert ApproximationarXiv:2610.00367v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models enable parameter scaling with limited per-token computation by activating only a small subset of experts for each token,→2 Oct 2026Forking: Sudden Overfitting Under ReplayarXiv:2610.00394v1 Announce Type: new Abstract: This paper studies forking, a generalization failure discovered in NanoGPT autoresearch. Under data replay, models with an over-encoding n-gram memory b→6 Oct 2026Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based PromptsarXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr→7 Oct 2026Who Wrote It Is Not Enough: Detecting Who Contributed the InsightarXiv:2610.07365v1 Announce Type: new Abstract: As LLMs increasingly assist scientific writing and peer review, detecting who wrote the text is no longer sufficient: we need to determine who contribut→8 Oct 2026Learning Situation-Conditioned Thinking Policies for Long-Term LLM AgentsarXiv:2610.09590v1 Announce Type: cross Abstract: Long-running autonomous agents must reuse accumulated reasoning experience without allowing explicit historical memory and LLM context to grow indefin→9 Oct 2026Evaluating Rubric Generation with Interventional TransferarXiv:2610.10809v1 Announce Type: new Abstract: Instance-specific rubrics are common in AI benchmarks where reliable evaluation requires specific expert knowledge. This approach is difficult to scale,→12 Oct 2026Can Language Models Play the Wikipedia Game?arXiv:2610.13948v1 Announce Type: new Abstract: Language models increasingly support or automate information retrieval from document collections too large to index. This task is difficult when it requ
CompanyNVIDIA8 recent entries1 Oct 2026Cycle-Aware Autoencoder with Cross-SignalConsistency for Railway Door Anomaly DetectionarXiv:2609.39035v1 Announce Type: cross Abstract: Passenger access doors are safety-critical subsystems in railway vehicles, yet detecting abnormal door behavior in real operation is challenging becau→6 Oct 2026Vision Transformer Ensembles for Panoramic Street SegmentationarXiv:2610.06063v1 Announce Type: new Abstract: Semantic segmentation of street panoramas can support detailed descriptions of urban environments, yet small datasets and unequal training costs make mo→6 Oct 2026TurboPairFormer: Fast and Stable Protein Folding Model Training with an Optimized Triangle Attention KernelarXiv:2610.05854v1 Announce Type: new Abstract: Triangular attention is a core computation in AlphaFold3-style biomolecular models, with cubic cost in token count. Its shared pair bias adds a gradient→6 Oct 2026A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac SimarXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor→7 Oct 2026WareFly-VLA: A Vision-Language-Action Framework for UAV Navigation and Human Tracking in Smart WarehousesarXiv:2610.08526v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved impressive results in robotic manipulation and ground-mobile navigation, yet language-conditioned co→7 Oct 2026Offline AI Modules: Voice-First Offline Architecture, Hardware Reference Stack, Quantization and BenchmarkingarXiv:2610.07026v1 Announce Type: new Abstract: The Offline AI Modules workstream enables practical, low-power, and community-accessible deployment of voice-first AI systems that operate fully offline→9 Oct 2026The Missing Fourth Term for the Emulation Tensor Memory Equilibrium (TME) Model: The Residue Deconstruction CostarXiv:2610.10924v1 Announce Type: cross Abstract: The Tensor-Memory Equilibrium (TME) model of 'FP8 is All You Need (Part 1)' calculates the execution time of Ozaki Scheme II emulation of fp64 as the →9 Oct 2026Demonstrating Arena 5.0: A Photorealistic ROS2 Simulation Framework for Developing and Benchmarking Social NavigationarXiv:2610.11220v1 Announce Type: new Abstract: Building upon the foundations laid by our previous work, this paper introduces Arena 5.0, the fifth iteration of our framework for robotics social navig