CompanyAnthropic8 recent entries2 Sept 2026MemoryWalker: Stop Training Agents on Contexts They Never SawarXiv:2609.00865v1 Announce Type: cross Abstract: Production agent harnesses such as Claude Code and Qwen-Agent compress context during rollout, but training under compression creates a conditioning p→10 Sept 2026Performance of Clinical AI System and Physicians and Frontier Language Models in primary care diagnosticsarXiv:2609.09070v1 Announce Type: cross Abstract: Clinical AI evaluation should encompass diagnosis and management after adaptive information gathering. We compared Doctorina, eight physicians and fou
CompanyOpenAI8 recent entries28 Jul 2026OpenAIs HealthBench in Action: Evaluating an LLM-Based Medical Assistant on Realistic Clinical QueriesarXiv:2509.02594v3 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) on their ability to generate high-quality, accurate, situationally aware answers to clinical questions→31 Jul 2026LayerRAG-Bench: A Cross-Layer Reliability Benchmark for Agentic Retrieval-Augmented GenerationarXiv:2607.27353v1 Announce Type: new Abstract: Agentic retrieval-augmented generation systems can produce answers that appear grounded while failing at the evidence, tool-contract, authorization, or →11 Aug 2026AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research GroupsarXiv:2608.08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows. H→24 Aug 2026Jokes Aside: Measuring the Semantic Distance of Double MeaningsarXiv:2608.21087v1 Announce Type: new Abstract: Large language models have significantly enriched the toolkit for computational humor research, particularly in the automated generation of jokes and pu→25 Aug 2026Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice PredictionarXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models→26 Aug 2026RENDER: Controlling Reader-Facing Evidence in LLM Memory EvaluationarXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem→1 Sept 2026Gurukul AI: An Interactive AI-Driven Educational Platform for Indian Education SystemarXiv:2608.28611v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) like ChatGPT and LLaMA have transformed AI-driven education, but these systems are predominantly train→23 Sept 2026DUMA-Bench: A Dual-Control Multi-Agent Benchmark for Evaluating LLM Agent SecurityarXiv:2609.24662v1 Announce Type: new Abstract: LLM-based agents increasingly operate in environments where they interact with users, tools, and external systems. Yet most security evaluations assume
CompanyGoogle8 recent entries15 Sept 2026MARCUS: An agentic, multimodal vision-language model for cardiac diagnosis and managementarXiv:2603.22179v2 Announce Type: replace Abstract: Cardiovascular disease remains the leading cause of global mortality, with progress hindered by human interpretation of complex cardiac tests. Curre→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→15 Sept 2026ClinAgent: A ReAct-Based Agent for Conversational Access to Clinical Trial InformationarXiv:2609.13860v1 Announce Type: new Abstract: Querying clinical trial registries remains a manual and error-prone process, requiring researchers to navigate large volumes of semi-structured data wit→16 Sept 2026EviScope: Paired Counterfactual Evidence Diagnostics for Faithful and Efficient Grounded Language ModelsarXiv:2609.17081v1 Announce Type: new Abstract: Grounded language-model systems are often evaluated by final answer accuracy, yet a correct answer can be unsupported, drawn from the wrong source, or p→22 Sept 2026Document Retrieval-Aware Chunking (D-RAC): Universal Retrieval-Aware Ingestion of Enterprise Documents via PDF Normalization and Multimodal Markdown ConversionarXiv:2609.24220v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems over enterprise knowledge bases must ingest heterogeneous document formats -- PDFs, Word documents, present→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 →1 Oct 2026EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific DiscoveryarXiv:2609.40340v1 Announce Type: new Abstract: Evolutionary search with large language models (LLMs) can stall when progress requires external knowledge the model lacks. Supplying relevant documents →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
CompanyMeta8 recent entries25 Sept 2026Agent Memory with Episodic Retrieval for Financial Decision-MakingarXiv:2609.28771v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong capabilities in financial analysis and reasoning, inspiring recent advances in agent-based trading→28 Sept 2026Stale-Document Poisoning: When Outdated Retrieval Overrides Correct Model AnswersarXiv:2609.31342v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is often used to address outdated knowledge by providing external evidence. But retrieval helps only when that evid→29 Sept 2026Identifying Temporal Features within Transcoders for Time Sensitive Factual RecallarXiv:2609.33183v1 Announce Type: cross Abstract: Large Language Models (LLMs) suffer from temporal misalignment, often due to the contradictory nature of their training corpora. While current mitigat→1 Oct 2026Re-ranking and Late Interaction Drive Retrieval Quality: A Controlled Comparison of RAG Strategies for Scientific Question AnsweringarXiv:2609.38473v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is now the standard way to ground Large Language Models (LLMs) in external knowledge, yet the design space of ret→1 Oct 2026Conformal Factuality Control for Multi-Hop Retrieval-Augmented GenerationarXiv:2609.38222v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can ground large language models in external evidence, but retrieved context does not guarantee that generated clai→2 Oct 2026HHR: Hierarchical Hash Retrieval for Efficient LLM GenerationarXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off→5 Oct 2026Output Language Confusion under Multilingual Prompt ContaminationarXiv:2610.02926v1 Announce Type: new Abstract: Standard factual benchmarks assume clean monolingual prompts and exact-match scoring, two assumptions that break simultaneously in real-world multilingu→7 Oct 2026Even Small Reasoners Should Quote Their Sources: Introducing the Pleias-RAG Model FamilyarXiv:2504.18225v2 Announce Type: replace Abstract: We introduce a new generation of small reasoning models for RAG, search, and source summarization. Pleias-RAG-350m and Pleias-RAG-1B are mid-trained
CompanyMistral8 recent entries20 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→26 Aug 2026Revelation ControlarXiv:2608.23860v1 Announce Type: cross Abstract: Revelation Control is the problem of choosing priced interventions that reveal hidden state only insofar as the revealed distinctions can change a con→27 Aug 2026A Layered Security Framework Against Prompt Injection in RAG-Based ChatbotsarXiv:2606.19660v2 Announce Type: replace-cross Abstract: Prompt injection is ranked as the most critical vulnerability in large language model (LLM) deployments by the OWASP Top 10 for LLM Applicatio→4 Sept 2026STAIR (STructure Aware Information Retriever): A novel dataset and LLM based retriever for document structure augmentationarXiv:2609.03874v1 Announce Type: new Abstract: Retrieval Augmented Generation (RAG) is a key component for generating accurate and hallucination free answers using Large Language Models (LLMs). LLMs →14 Sept 2026EAR: Entity-Aware Partitioning Approach for Retrieval-Augmented Generation DevelopmentarXiv:2609.12268v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) can improve knowledge-intensive question answering, but the first design choice is easy to overlook: how should the→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→24 Sept 2026Computation Over Geometry: Meaning Identity Is Computed, Not Shipped in the EmbeddingsarXiv:2609.28290v1 Announce Type: new Abstract: Meaning identity (whether two sentences say the same thing after wording changes) is treated in retrieval and RAG as a geometric fact about independentl
CompanyxAI8 recent entries10 Apr 2026Illocutionary Explanation Planning for Source-Faithful Explanations in Retrieval-Augmented Language ModelsarXiv:2604.06211v1 Announce Type: cross Abstract: Natural language explanations produced by large language models (LLMs) are often persuasive, but not necessarily scrutable: users cannot easily verify→21 Apr 2026Emergent Misalignment via In-Context Learning: Narrow in-context examples can produce broadly misaligned LLMsarXiv:2510.11288v4 Announce Type: replace Abstract: Recent work has shown that narrow finetuning can produce broadly misaligned LLMs, a phenomenon termed emergent misalignment (EM). While concerning, →28 Apr 2026XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented GenerationarXiv:2604.24623v1 Announce Type: new Abstract: Graph-based Retrieval-Augmented Generation (GraphRAG) extends traditional RAG by using knowledge graphs (KGs) to give large language models (LLMs) a str→28 Jul 2026OpenAIs HealthBench in Action: Evaluating an LLM-Based Medical Assistant on Realistic Clinical QueriesarXiv:2509.02594v3 Announce Type: replace-cross Abstract: Evaluating large language models (LLMs) on their ability to generate high-quality, accurate, situationally aware answers to clinical questions→4 Aug 2026When Retrieval Helps and Distracts: Evaluating Evidence-Generating LLMs for Biomedical Claim VerificationarXiv:2608.01409v1 Announce Type: new Abstract: Biomedical fact-checking systems must do more than predict whether a claim is supported, contradicted, or unaddressed: they should also produce evidence→11 Aug 2026Bounding Hallucinations: Merlin-Arthur Protocols for Mutual-Information Bounds in Language ModelsarXiv:2512.11614v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) relies on retrieved context to guide large language models (LLM), yet treats the retrieval as a heuristic→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→1 Sept 2026Answer Bubbles: Information Exposure in AI-Mediated SearcharXiv:2603.16138v2 Announce Type: replace-cross Abstract: Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these sys
CompanyDeepSeek8 recent entries18 Sept 2026BioPhys-Bridge: A Benchmark for Interdisciplinary Scientific Reasoning in Physics-Grounded Biological ResearcharXiv:2609.19180v1 Announce Type: new Abstract: Language models face unique challenges in analyzing interdisciplinary scientific research literature. In biophysics research, faithful answers require g→22 Sept 2026Balancing Reasoning and Hardware Constraints in RAG Pipelines for Ukrainian Multi-Domain Document UnderstandingarXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise→23 Sept 2026DUMA-Bench: A Dual-Control Multi-Agent Benchmark for Evaluating LLM Agent SecurityarXiv:2609.24662v1 Announce Type: new Abstract: LLM-based agents increasingly operate in environments where they interact with users, tools, and external systems. Yet most security evaluations assume →24 Sept 2026Automated Extraction of Records of Processing Activities (RoPA) Using Hybrid RAG and Locally Deployed Large Language ModelsarXiv:2609.27359v1 Announce Type: new Abstract: Vietnam's Personal Data Protection Law (Law No. 91/2025/QH15) and Decree No. 356/2025/ND-CP, effective January 1, 2026, require organizations to establi→7 Oct 2026ServeLearnBench: How Well Can Agents Self-Improve from Serving Experience?arXiv:2610.07792v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct→12 Oct 2026Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QAarXiv:2610.13128v1 Announce Type: new Abstract: Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-→12 Oct 2026Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border CommunitiesarXiv:2610.12610v1 Announce Type: cross Abstract: Ethnic and cultural identities rarely align with political borders, a tension made sharper by migration and long-standing cross-border ties. Communiti→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 entries18 Aug 2026The Commercial Tax: Rent-vs-Own Blind Spots in Multi-Hop Retrieval BenchmarksarXiv:2608.16096v1 Announce Type: cross Abstract: Enterprises connect language models to their own data through retrieval. The benchmarks that rank multi-hop retrieval systems leave out two facts a bu→21 Aug 2026From Retrieved Context to Runtime Control: Adaptive Compression for Edge-based RAGarXiv:2608.19535v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves language-model responses by grounding generation in external passages, which comes with overhead: retrieve→25 Aug 2026Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team MeetingsarXiv:2608.22108v1 Announce Type: new Abstract: Breast Cancer Multidisciplinary Team (MDT) meetings manage increasingly complex cases under considerable time pressure, and documentation requirements c→10 Sept 2026Reading a Legal Question Word by Word: Embedding Trajectories of 2,144 Vietnamese Legal HeadlinesarXiv:2609.08372v2 Announce Type: replace Abstract: A dense retriever encodes a question as one vector, but the question arrives one word at a time. We read 2,144 held-out headlines from Thu Vien Phap→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→15 Sept 2026Empirical Evaluation of Open-Source Large Language Models for Retrieval-Augmented Generation in ESG DomainarXiv:2609.15242v1 Announce Type: new Abstract: Environmental, Social, and Governance (ESG) reporting is critical for corporate accountability, with Large Language Models (LLMs) and Retrieval-Augmente→17 Sept 2026Beyond Static RAG: An Adaptive, Tri-Metric Routing Framework for Efficient Long-Context Inference on Commodity GPUsarXiv:2609.17564v1 Announce Type: new Abstract: Deploying retrieval-augmented generation (RAG) on commodity GPUs such as the NVIDIA T4 (16 GB VRAM) exposes a practical failure mode we call the Compres→22 Sept 2026Balancing Reasoning and Hardware Constraints in RAG Pipelines for Ukrainian Multi-Domain Document UnderstandingarXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise