CompanyAnthropic8 recent entries31 Aug 2026SciReC: Diagnostic Evaluation of Multimodal, Multi-Turn Relational Reasoning with Adaptive InteractionarXiv:2608.27461v1 Announce Type: new Abstract: Relational reasoning requires the process of perceptual understanding, comparing, and integrating the underlying relationships between concepts. This ab→1 Sept 2026SHADOWBENCH: Toward Reliable Automatic Evaluation of Semantic Alignment in AutoformalizationarXiv:2608.29270v1 Announce Type: cross Abstract: Autoformalization translates informal mathematical theorems into code for proof assistants such as Lean. A central challenge is that current evaluatio
CompanyOpenAI8 recent entries2 Sept 2026Sources of Truth: A Multi-Platform, Multilingual Audit of Citations in AI Mental Health Information QueriesarXiv:2609.00319v1 Announce Type: cross Abstract: Online health information seeking is shifting from keyword search, where users consider a ranked list of links, to conversational systems that compose→2 Sept 2026Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain SensingarXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud→7 Sept 2026Substrate-Aware AI Agents: Execution Context as a First-Class InputarXiv:2609.05232v1 Announce Type: new Abstract: Autonomous AI agents increasingly select actions in environments whose memory, execution-time, runtime, compute, and operational constraints determine w→10 Sept 2026Flawed but Memorable: Student Critical Reception of Interest-Personalized GenAI Analogies in Computing EducationarXiv:2609.06095v1 Announce Type: cross Abstract: Motivation: Undergraduate computing students increasingly turn to generative AI (GenAI) tools to understand abstract concepts through analogies. Analo→15 Sept 2026Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type→17 Sept 2026Benchmarking Large Language Models for Biomedical Relation ExtractionarXiv:2609.19071v1 Announce Type: new Abstract: Extracting SNP-phenotype associations from biomedical literature is vital but challenging. We benchmarked diverse NLP models, including MLMs, hybrid arc→18 Sept 2026Inference-Engine Fingerprinting Attacks are Practical: Exploring Model-Driven Environmental Discovery, Exploitation, and EscapearXiv:2609.20614v1 Announce Type: cross Abstract: Frontier AI models are rapidly gaining the ability to exploit vulnerabilities in complex pieces of software. The risk is not theoretical, as evidenced→25 Sept 2026Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486v5 Announce Type: replace Abstract: This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, sp
CompanyGoogle8 recent entries24 Aug 2026ARQ: Agentic CodeQL Query Refinement for C/C++ Vulnerability DetectionarXiv:2608.20637v1 Announce Type: cross Abstract: Static analyzers have been widely adopted for vulnerability detection in C/C++ programs. Query-based static analyzers (e.g., CodeQL) encode vulnerable→25 Aug 2026Dual-Grained Agent Memory and Shapley Context Attribution for Multimodal Agentic LearnerarXiv:2608.23268v1 Announce Type: new Abstract: Frontier multimodal large language models (MLLMs) deliver impressive perception yet still falter on scientific and mathematical reasoning. Parameter-lev→25 Aug 2026Beyond Benchmarking: Scenario-Based Evaluation of Large Language Models for Personalized LearningarXiv:2509.05346v3 Announce Type: replace Abstract: While large language models (LLMs) are increasingly being adopted to support personalized learning, there remains limited understanding of how their→7 Sept 2026Substrate-Aware AI Agents: Execution Context as a First-Class InputarXiv:2609.05232v1 Announce Type: new Abstract: Autonomous AI agents increasingly select actions in environments whose memory, execution-time, runtime, compute, and operational constraints determine w→10 Sept 2026Safety boundary maintenance in consumer AI systems responding to pediatric health queries: a cross-platform benchmark evaluation under naturalistic and adversarially pressured conditionsarXiv:2601.09721v2 Announce Type: replace-cross Abstract: Consumer artificial intelligence chatbots are now accessed by hundreds of millions of users seeking health information, yet systematic evaluat→15 Sept 2026Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type→17 Sept 2026Benchmarking Large Language Models for Biomedical Relation ExtractionarXiv:2609.19071v1 Announce Type: new Abstract: Extracting SNP-phenotype associations from biomedical literature is vital but challenging. We benchmarked diverse NLP models, including MLMs, hybrid arc→30 Sept 2026Evaluating the Evaluators: Diagnosing Large Multimodal Models for AI-Generated Image AssessmentarXiv:2609.37576v1 Announce Type: new Abstract: With the rapid advancement of text-to-image (T2I) generation, robust evaluation becomes critical yet challenging, as traditional metrics fail to capture
CompanyMeta8 recent entries2 Oct 2026Meta-Multi-Agent Reinforcement Learning for Fast Adaptation of Interactive Policies with Applications to Autonomous DrivingarXiv:2610.00705v1 Announce Type: new Abstract: This paper develops a meta-multi-agent reinforcement learning (meta-MARL) framework to enable fast adaptation of interactive policies in a multi-agent s→2 Oct 2026HADRec: A Hierarchy-Aware Drug Recommendation Framework by Fusing Molecular Knowledge and Electronic Health RecordarXiv:2610.00984v1 Announce Type: new Abstract: Accurate medication recommendation is central to clinical decision-making, directly determining therapeutic efficacy and patient safety. However, existi→2 Oct 2026Beyond Linear Concepts: Discovering and Aligning Non-Linear Concept Manifolds in Large Language ModelsarXiv:2610.01821v1 Announce Type: new Abstract: Understanding information processing in large language models (LLMs) requires dissecting the geometric organization of their internal token representati→2 Oct 2026Attention Manifolds: Steering or Blocking Language Models by Editing Learned B-Spline SurfacesarXiv:2610.00257v1 Announce Type: new Abstract: In standard transformer attention, a source token sends the same value vector to every receiver. The query determines how much to attend but not what to→5 Oct 2026From Benchmarks to Production: A Text-to-SQL System for Complex Financial DataarXiv:2610.03524v1 Announce Type: new Abstract: General-purpose Text-to-SQL systems achieve strong performance on academic benchmarks like Spider and BIRD, where schemas are relatively shallow and col→6 Oct 2026Ontology Concept Overlap as a Training Signal: Knowledge-Grounded Reinforcement Learning for Clinical Question AnsweringarXiv:2610.06360v1 Announce Type: cross Abstract: Reinforcement learning post-training for language models relies on two reward designs: human preferences (RLHF, DPO) and binary verifiers (RLVR). Clin→7 Oct 2026Does the Model Use the Feature? Separating Steering from Mechanism in LLMsarXiv:2610.07270v1 Announce Type: new Abstract: Internal features in LLMs are often interpreted as mechanisms when they track a concept and their manipulation changes a related behavior. Yet steering →12 Oct 2026LLMail-Inject: A Dataset from a Realistic Adaptive Prompt Injection ChallengearXiv:2506.09956v2 Announce Type: replace-cross Abstract: Indirect prompt injection attacks exploit a fundamental weakness of LLMs: executing unauthorized tasks from untrusted sources. Despite the pra
CompanyMistral8 recent entries31 Jul 2026STEREODISCO: Discovering Stereotypicality in LLMsarXiv:2607.27824v1 Announce Type: cross Abstract: LLMs encode, convey, and perpetuate stereotypes. Prior computational research focuses on a small set of semantic axes investigated in social psycholog→7 Aug 2026PoolBench: A Benchmark for Pooling Strategies in Concept Representation Evaluation for Decoder-Only LLMsarXiv:2608.05162v1 Announce Type: new Abstract: Pooling is a consequential but under-examined design choice in decoder-only concept representation work: practitioners must collapse token-level hidden →20 Aug 2026Pedagogical AI in Mental Health: A Tri-Stream Fine-Tuned LLM Framework for Automated Clinical Supervision and Risk TriagearXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a 'supervision gap' where novice therapists manage high→1 Sept 2026Test-Time Training with Next-Token PredictionarXiv:2606.21803v2 Announce Type: replace Abstract: Next-token prediction is the self-supervised signal that trains language models, and every observed prompt token provides the same signal at test ti→14 Sept 2026Automated Detection and Structuring of Social Tipping Point Evidence in Climate related Documents: A Modular AI FrameworkarXiv:2609.12254v1 Announce Type: new Abstract: The climate literature has grown faster than review teams can read it. That gap matters most for a concept like the environmental social tipping point, →17 Sept 2026Benchmarking Large Language Models for Biomedical Relation ExtractionarXiv:2609.19071v1 Announce Type: new Abstract: Extracting SNP-phenotype associations from biomedical literature is vital but challenging. We benchmarked diverse NLP models, including MLMs, hybrid arc→18 Sept 2026Digital Twins for Opinion Dynamics: A Generative LLM Framework for Social NetworksarXiv:2609.19913v1 Announce Type: new Abstract: The study of opinion dynamics in social networks is one of the key challenges in computational social science with direct relevance to understanding pol→30 Sept 2026Causal and Interpretable Structures in LLM Compositional TasksarXiv:2609.35970v1 Announce Type: cross Abstract: Large language models are able to solve tasks whose answers depend on not only individual input tokens, but also on relations among them. How is such
CompanyxAI8 recent entries1 Sept 2026Integrating attention into explanation frameworks for language and vision transformersarXiv:2508.08966v2 Announce Type: replace Abstract: The attention mechanism lies at the core of the transformer architecture, providing an interpretable model-internal signal that has motivated a grow→4 Sept 2026Differentiable Interval Bottlenecks for Interpretable Anomaly Detection in Numerical DataarXiv:2609.03878v1 Announce Type: cross Abstract: Reconstruction-based anomaly detectors are accurate but opaque: a deep autoencoder flags a sample without telling a practitioner which feature ranges →7 Sept 2026From Interpretability Methods to Interpretable ModelsarXiv:2609.05399v1 Announce Type: new Abstract: More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and c→15 Sept 2026Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type→28 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→5 Oct 2026Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain ShiftarXiv:2610.02364v1 Announce Type: new Abstract: Explainability is increasingly required for perception models in intelligent vehicles, yet whether explanations remain faithful under driving domain shi→8 Oct 2026Revisiting Explainable AI through Model-Independent Concept DictionariesarXiv:2610.10301v1 Announce Type: new Abstract: Modern applications of AI rely on increasingly complex models. Explainable AI (XAI) has emerged as a set of techniques aimed at improving model transpar
CompanyDeepSeek8 recent entries1 May 2026Math Education Digital Shadows for facilitating learning with LLMs: Math performance, anxiety and confidence in simulated students and AIsarXiv:2604.27618v1 Announce Type: new Abstract: To enhance LLMs' impact on math education, we need data on their mathematical prowess and biases across prompts. To fill this gap, we introduce MEDS (Ma→6 May 2026VisInject: Disruption != Injection -- A Dual-Dimension Evaluation of Universal Adversarial Attacks on Vision-Language ModelsarXiv:2605.01449v1 Announce Type: cross Abstract: Universal adversarial attacks on aligned multimodal large language models are increasingly reported with attack success rates in the 60-80% range, sug→29 May 2026Empathic Prompting: Non-Verbal Context Integration for Multimodal LLM ConversationsarXiv:2510.20743v2 Announce Type: replace-cross Abstract: We present Empathic Prompting, a novel framework for multimodal human-AI interaction that enriches Large Language Model (LLM) conversations wi→10 Jun 2026Moonshine: An Autonomous Mathematical Research Agent Centered on Conjecture GenerationarXiv:2606.10806v1 Announce Type: new Abstract: Moonshine is an autonomous agent whose central objective is to generate mathematical conjectures. Its core capability is to extract structure from class→24 Jul 2026What, Where, and How: Disentangling the Roles of Task, Language, and Model in Code Model RepresentationsarXiv:2607.21491v1 Announce Type: new Abstract: Do independently trained language models come to represent the same thing in the same way? We answer for code, extending a recently introduced concept-c→18 Aug 2026Revisiting the Performance of Generative Artificial Intelligence on Introductory Object-Oriented Programming Assessments: Insights from 2026arXiv:2608.16318v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence (GenAI) have substantially improved the ability of large language models (LLMs) to generate and →24 Aug 2026Toward Vision Language Model-based Assessment of Clinical Quality and Usability of LGE-MR Images for Cardiac Ablation PlanningarXiv:2608.21180v1 Announce Type: cross Abstract: LGE cardiac MRI is widely used for left atrial fibrosis assessment and ablation planning in atrial fibrillation patients as knowledge of fibrotic tiss→16 Sept 2026Test-Time Unlearning via Sparse AutoencoderarXiv:2609.16229v1 Announce Type: cross Abstract: Machine unlearning aims to remove specific knowledge from a trained large language model (LLM) without retraining from scratch. Existing methods modif
CompanyNVIDIA8 recent entries14 Apr 2026VTC: DNN Compilation with Virtual Tensors for Data Movement EliminationarXiv:2604.09558v1 Announce Type: cross Abstract: With the widening gap between compute and memory operation latencies, data movement optimizations have become increasingly important for DNN compilati→27 Apr 2026Incentivizing Neuro-symbolic Language-based Reasoning in VLMs via Reinforcement LearningarXiv:2604.22062v1 Announce Type: new Abstract: There are 7,407 languages in the world. But, what about the languages that are not there in the world? Are humans so narrow minded that we don't care ab→15 Jul 2026HPC-Enabled Video-based Coastal Wave Parameter Estimation Using V-JEPA and Deep Spatiotemporal LearningarXiv:2607.11998v1 Announce Type: cross Abstract: High deployment cost, poor spatial coverage and susceptibility to storm conditions are all challenges faced by traditional in-situ methods. This paper→10 Aug 2026Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-TuningarXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class →11 Aug 2026LGNNIC: Acceleration of Large-Scale GNN Training using SmartNICsarXiv:2608.07733v1 Announce Type: cross Abstract: Graph Neural Networks (GNNs) are widely used across domains such as natural sciences, social network analysis, chip design, and recommendation systems→17 Sept 2026Lecture notes on Physics Informed Neural Networks, Neural Operators, and their applicationsarXiv:2609.17638v1 Announce Type: cross Abstract: This is the set of lecture notes for the PhD course href{https://www.unibz.it/en/faculties/engineering/phd-computer-science/study-course-offering/2025→22 Sept 2026HumynexSurg-1: A Curated Expert Liposuction DatasetarXiv:2609.23885v1 Announce Type: cross Abstract: Robot foundation models learn manipulation from large demonstration corpora, but surgery is missing from those corpora: across the 780-hour Open-H sur→1 Oct 2026Decode-Latency Feedback Prefill: A Model-Free Controller and Its Generalization LimitsarXiv:2609.38386v1 Announce Type: new Abstract: Concurrent autoregressive inference creates a fundamental interference problem: prefilling a newly arrived long prompt can delay tokens for requests tha