CompanyAnthropic8 recent entries1 Oct 2026RAIM: Robust Aggregation of Inexpensive Models for Hallucination DetectionarXiv:2609.39229v1 Announce Type: cross Abstract: Automatic evaluation of faithfulness increasingly relies on a large language model acting as a judge, yet the most reliable judges are proprietary fro→2 Oct 2026OR for AI That Does OR: Routing LLMs up the Escalator inside the OSCAR FrameworkarXiv:2610.00912v1 Announce Type: new Abstract: Large language models can translate business descriptions into optimization models, but executable code may misrepresent constraints or objectives. A so
CompanyOpenAI8 recent entries14 Aug 2026Reliability-Aware Sexism Detection: Combining DPO with Annotator Agreement and Token-Level Confidence ScoringarXiv:2608.12330v1 Announce Type: new Abstract: The detection of online sexism remains an open problem. Sexism detection is inherently subjective, yet most existing systems reduce multi-annotator labe→18 Aug 2026Plausible but Not Valid: A Psychometric Audit of LLMs as Synthetic Survey RespondentsarXiv:2608.14606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as synthetic survey respondents, but existing evaluations ask whether answers look plausible at the→26 Aug 2026Can large language models assist choice modelling? Insights into prompting strategies and current models' capabilitiesarXiv:2507.21790v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are becoming widely used to support various workflows across different disciplines, yet their potential in discre→12 Sept 2026Can LLMs Follow Medical Expert Logic? A Benchmark for Hierarchical Logical Consistency in Risk-of-Bias AssessmentarXiv:2609.11185v1 Announce Type: new Abstract: Evidence-based medicine demands strict logical consistency, yet current evaluations of large language models (LLMs) prioritize superficial label matchin→22 Sept 2026Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated ResumesarXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t→25 Sept 2026ASIRF: An Agentic Framework for Context-Dependent Sensitive Information RedactionarXiv:2609.29191v1 Announce Type: new Abstract: Sensitive information is defined by domain and intent, not a universal category, yet redaction systems such as privacy filters and named-entity recogniz→28 Sept 2026Muslim: A Deployed Arabic Voice AI Platform for Grounded Islamic KnowledgearXiv:2609.31511v1 Announce Type: new Abstract: We present Muslim, a production Arabic voice AI platform serving grounded, sourced Islamic knowledge to real users. Beyond a real-time voice pipeline (N→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
CompanyGoogle8 recent entries22 Sept 2026Fairness Beyond Anonymization? Demographic Leakage in German LLM-Generated ResumesarXiv:2609.22188v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into AI-assisted hiring pipelines, including automated resume generation and screening. Under t→25 Sept 2026CRISS: A Retrieval-Augmented AI Chatbot for Assisting Cancer RegistrarsarXiv:2609.29075v1 Announce Type: new Abstract: Cancer registrars, including Oncology Data Specialists (ODSs), must interpret complex and frequently updated coding and staging standards. We developed →29 Sept 2026Probe to Act: Elevating Browser-Use Agent via Active Visual ProbingarXiv:2609.33646v1 Announce Type: cross Abstract: Browser-use agents require seamless alignment between structured web metadata and visual information, while preserving relevant context across long in→30 Sept 2026Evidence-Guided Schema Normalization for Temporal Tabular ReasoningarXiv:2512.00329v2 Announce Type: replace-cross Abstract: Temporal reasoning over evolving semi-structured tables poses a challenge to current QA systems. We propose an approach that recasts the task →2 Oct 2026DuplexSpeechBench-Document Grounding: Benchmarking Document Grounding and Hallucinations in Voice AgentsarXiv:2610.00316v1 Announce Type: cross Abstract: Voice agents enable low-latency, natural interaction, yet their ability to faithfully ground responses in external documents remains underexplored. We→5 Oct 2026GISTBench: Evaluating LLM User Understanding via Evidence-Based Interest VerificationarXiv:2603.29112v2 Announce Type: replace Abstract: We introduce GISTBench, a benchmark for evaluating Large Language Models' (LLMs) ability to understand users from their interaction histories in rec→5 Oct 2026Do Large Language Models Know Colombian Law? A Reliability Benchmark for the Colombian Legal SystemarXiv:2610.03639v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support legal practice, education, and research, yet their reliability in national legal systems o→8 Oct 2026A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model BehaviorarXiv:2602.02639v2 Announce Type: replace-cross Abstract: LLM self-explanations are often presented as a promising tool for AI oversight, yet their faithfulness to the model's true reasoning process i
CompanyMeta8 recent entries1 Oct 2026Network-based Spatial Context Retrieval for Open-weight LLMs: A Faithfulness Benchmark for Grounded Geographic ReasoningarXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor→1 Oct 2026NAQD Env: A benchmark for selective withdrawal in language agentsarXiv:2609.38460v1 Announce Type: new Abstract: Language agents must revise planned actions when evidence changes, permission is revoked, or a stop instruction arrives. A useful response is selective:→1 Oct 2026MILO: Automated Harness Discovery via Orchestrated Multi-Agent EvolutionarXiv:2609.38349v1 Announce Type: cross Abstract: Modern agentic systems combine an AI model with a harness that controls execution and environmental interactions. Harness design strongly affects long→5 Oct 2026Silent Dissent: LLM Agents That Yield to the Majority Still Represent Their Original PremisearXiv:2610.02702v1 Announce Type: new Abstract: Multi-agent debate is increasingly used to reach consensus among LLM agents, yet agents often yield to a unanimous majority. When an agent changes its a→5 Oct 2026Prompted to Discriminate: Generalizing Malicious-Input Probes in the WildarXiv:2610.02413v1 Announce Type: new Abstract: LLM agents increasingly rely on activation probes as runtime monitors for prompt injection, jailbreaks, and unsafe requests, reading the model's own hid→7 Oct 2026Defense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced SycophancyarXiv:2610.07403v1 Announce Type: new Abstract: Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-→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→9 Oct 2026NOMOS: Compiling Written Policies into Statically Verified Tool-Call Gates for LLM AgentsarXiv:2610.11030v1 Announce Type: cross Abstract: Tool-using LLM agents violate the policies they are deployed to enforce, often silently. Prior defenses hand-write rules, query an LLM verifier per ac
CompanyMistral8 recent entries11 Sept 2026OpenDiscoveryTrace: Process Traces for Evaluating AI Scientist WorkflowsarXiv:2609.09203v1 Announce Type: new Abstract: Existing benchmarks for autonomous AI scientists evaluate only final outputs---generated code, hypotheses, or papers---yet discard the reasoning process→15 Sept 2026TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOpsarXiv:2609.14762v1 Announce Type: cross Abstract: Cloud-hosted large language models (LLMs) are increasingly used for root cause analysis (RCA) in AIOps pipelines, but they introduce data privacy risk→17 Sept 2026Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to RecruitmentarXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these c→22 Sept 2026Does the Truthfulness Signal Survive Code-Mixing? Probing Hidden States for Hallucination Detection in HinglisharXiv:2609.22138v1 Announce Type: new Abstract: Hidden-state hallucination probing - training a linear classifier on an LLM's internal activations to detect whether a generated answer is faithful to t→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→23 Sept 2026Component Type, Not Reconstruction Error, Predicts Attention Quantization SensitivityarXiv:2609.26173v1 Announce Type: new Abstract: Many post-training quantization (PTQ) methods use layer-wise reconstruction, second-order proxy objectives, or activation-aware transformations to reduc→25 Sept 2026Combating Instruction Conflict via Energy-Driven Latent Conflict DetectionarXiv:2609.08646v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed with hierarchical instructions, yet they remain vulnerable to conflicts in which user directi→8 Oct 2026Quad-State Safety Evaluation of Open-Weight Large Language Models on Non-Canonical InputsarXiv:2610.09033v1 Announce Type: new Abstract: Standard safety evaluations of large language models assess harmful requests written in canonical plain text, while models in real-world deployment rout
CompanyxAI8 recent entries15 Apr 2026A Two-Stage LLM Framework for Accessible and Verified XAI ExplanationsarXiv:2604.12543v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to translate the technical outputs of eXplainable Artificial Intelligence (XAI) methods into accessib→20 Apr 2026QuantSightBench: Evaluating LLM Quantitative Forecasting with Prediction IntervalsarXiv:2604.15859v1 Announce Type: cross Abstract: Forecasting has become a natural benchmark for reasoning under uncertainty. Yet existing evaluations of large language models remain limited to judgme→5 May 2026Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical TasksarXiv:2605.01417v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insuff→4 Jun 2026Bypassing Prompt Guards in Production with Controlled-Release PromptingarXiv:2510.01529v3 Announce Type: replace Abstract: Ball et al. recently established that prompt filtering for AI alignment faces a fundamental barrier: under standard cryptographic assumptions, no fi→9 Jul 2026Memory Scarcity, Open Models, and the Restructuring of the AI Industry, 2026-2030 -- A quantitative scenario analysis of inference economics, training-cost divergence, and infrastructure solvencyarXiv:2607.07207v1 Announce Type: cross Abstract: We analyze how four forces restructure the AI industry over 2026-2030: the DRAM/HBM price surge, frontier-capable open-weight models (GLM-5.2), rapid →11 Aug 2026Harmful Content Is Not Enough: Continuation Framing Moderates In-Context Emergent MisalignmentarXiv:2608.08212v1 Announce Type: new Abstract: In-context learning (ICL) can induce emergent misalignment (EM), where narrow misaligned examples alter answers to unrelated questions. Existing prompts→13 Aug 2026A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBencharXiv:2608.12138v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but s→15 Sept 2026Trustworthy, Explainable, and Sustainable Decentralized Intelligence for 6G NetworksarXiv:2609.13872v1 Announce Type: cross Abstract: As 6G networks transition from theoretical frameworks into operational realities, artificial intelligence (AI) evolves from an add-on optimization too
CompanyDeepSeek8 recent entries21 Aug 2026OenoBench: A Wine-Domain Benchmark for Knowledge-Grounded Evaluation of Large Language ModelsarXiv:2608.20106v1 Announce Type: new Abstract: We introduce OenoBench, a wine-domain knowledge benchmark of 3,266 multiple-choice questions across six pillars (regions, grape varieties, viticulture, →26 Aug 2026Can large language models assist choice modelling? Insights into prompting strategies and current models' capabilitiesarXiv:2507.21790v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are becoming widely used to support various workflows across different disciplines, yet their potential in discre→1 Sept 2026Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning EnvironmentarXiv:2508.04865v4 Announce Type: replace Abstract: Large language models (LLMs) already excel at writing code in high-resource languages such as Python and JavaScript, yet stumble on low-resource lan→4 Sept 2026GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation ModelsarXiv:2606.12821v2 Announce Type: replace Abstract: Environmental scientists spend disproportionate effort on data wrangling rather than analysis. New AI agents can be a helpful tool, but no benchmark→15 Sept 2026Grounded Adjudication of Variations across Extracted TimeLines (GAVEL): Comparing Clinical Timelines Against Their Case ReportsarXiv:2609.13475v1 Announce Type: new Abstract: Existing pipelines for clinical timeline extraction from case reports are evaluated using an expert reference and are limited by imperfect reference ann→15 Sept 2026Exploring Automated Vulnerability Identification in JavaScript Code Using Large Language ModelsarXiv:2609.13816v1 Announce Type: cross Abstract: JavaScript powers approximately 98.8% of all websites, making vulnerabilities in its code a significant security risk, yet existing detection approach→17 Sept 2026Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to RecruitmentarXiv:2609.18106v1 Announce Type: cross Abstract: Open-weight large language models are rapidly entering hiring pipelines, yet their discriminatory failure modes -- and the regulatory exposure these c→9 Oct 2026Mine Odyssey: Benchmarking Spatial Agentic Intelligence in the WildarXiv:2610.11328v1 Announce Type: new Abstract: Advances in foundation models are driving efforts to introduce agents to assist people in the physical world. Such agents require agentic spatial intell
CompanyNVIDIA8 recent entries15 Sept 2026TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOpsarXiv:2609.14762v1 Announce Type: cross Abstract: Cloud-hosted large language models (LLMs) are increasingly used for root cause analysis (RCA) in AIOps pipelines, but they introduce data privacy risk→15 Sept 2026Salesforce Koa: An Enterprise Language Model for Agentic Tool UsearXiv:2609.15066v1 Announce Type: cross Abstract: We present Salesforce Koa, an enterprise language model built by post-training the open-weight Nemotron-3-Super-120B foundation model with reinforceme→17 Sept 2026Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud ContinuumarXiv:2609.18283v1 Announce Type: new Abstract: As telecommunication networks evolve toward autonomous 5G-Advanced and 6G operations, agentic artificial intelligence (AI) workflows, where large langua→23 Sept 2026Hill Sampling for Test-Time Scaling: A Simple and Better Alternative to Repeated Sampling, Evolution, and TrainingarXiv:2609.25510v1 Announce Type: new Abstract: Large language models (LLMs) can improve solutions to verifiable scientific and algorithmic problems by spending additional computation at test time. Re→24 Sept 2026Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware ConstraintsarXiv:2609.28007v1 Announce Type: new Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents→30 Sept 2026Mixture-of-Kittens: MoE Megakernel for NVL72sarXiv:2609.36070v1 Announce Type: cross Abstract: AI accelerator systems are rapidly consolidating into scale-up architectures, where tens to thousands of GPUs communicate over high-bandwidth, single-→1 Oct 2026Role-guided Speaker Deletion Verification in Clinical Psychiatry Speech Recordings with Audio Language ModelsarXiv:2609.38491v1 Announce Type: new Abstract: Clinical research in psychiatry increasingly relies on large scale collection of spoken language data to identify acoustic and linguistic biomarkers. Ye→2 Oct 2026Fast Polynomial Transcendentals for LLMsarXiv:2610.00049v1 Announce Type: new Abstract: Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardwa