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Autonomous Research for Open-Ended Problems: A Case Study on Telecom Ticket Retrieval

Case study shows autonomous LLM research reaches 90% of SOTA on telecom ticket retrieval in 10 weeks versus 10 months human work.

The paper explores adapting autonomous research to open-ended, industry-grade ML problems through a telecom ticket retrieval case study with commercial and open-source agents. Autonomous research reached 90% of state-of-the-art performance (0.34 vs. 0.38 Recall@1) in 10 weeks versus 10 months of human work, at up to $200 per Cursor campaign. The authors find agents excel at narrow hyperparameter optimization but lack human-like intuition, recommending human-agent collaboration.

arXiv cs.AI / cs.LG / cs.CL · 4d agoAI research

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

Toward an Empirical Probabilistic Risk Manifestation Model of Organizational Cybersecurity in SMEs

Empirical study of 22 SME security assessments builds a probabilistic risk model and shows assessments can be cut 24-45% while retaining most critical findings.

Researchers analyzed 281 validated security findings from 22 real-world SME cybersecurity assessments conducted over two years via a pro bono university clinic. They derived an empirical Risk Manifestation Model linking eight organizational security functions to two exposure conditions, five attack mechanisms, and six outcome categories, using probability propagation to identify dominant risk pathways. The dominant pathway runs from asset exposure to credential compromise to unauthorized access, stable under leave-one-organization-out analysis. Retaining six functions reduces assessment burden by 24% while preserving 97% of critical findings; five functions cut burden 45% while preserving 89% of critical findings.

arXiv cs.CR · 2d agoResearch

Recorded Future Launches Impact and Metrics Dashboard

Recorded Future releases an Impact and Metrics Dashboard aggregating risk-reduction, detection, and analyst-efficiency metrics for customer leadership reporting.

The dashboard pulls data from a customer's environment, alerts, integrations, threat detections, and analyst activity into six metric areas: platform-wide security value, threat prioritization, threat detection, digital risk protection, account and credential monitoring, and Recorded Future AI and Insikt Group research usage. It is available now to all Recorded Future customers, who are advised to configure Priority Intelligence Requirements in Settings so reporting maps to their intelligence program. The vendor cites its 2025 ROI Report across nearly 300 customers reporting 351.3% annual ROI and says customers aligning alerting to PIRs identified new threats 65% faster.

Recorded Future · 23d agoTools

Engineered Persuasion: Evaluating Personalized Pretexts in LLM-Generated Spear Phishing

A study of 180 US workers found each LLM phishing personalization level raised click-intention odds by 28%, but credibility depends on context fit.

The arXiv paper evaluates how personalized pretexts in LLM-generated spear phishing affect perceived credibility, using 180 US working adults across 1,436 evaluations of emails with four cumulative personalization levels, from workplace context to shared-project details. Convincingness rose 2.40 points per level in sensitivity analysis and click-intention odds increased 28% per level, while non-clickers shifted toward deleting rather than reporting. Qualitative coding showed details matching the recipient's role and routines supported credibility, whereas incorrect, vague, or channel-inappropriate details raised suspicion. The authors argue personalization effectiveness depends on pretext fit, with implications for workplace security training.

arXiv cs.CR · 12d agoResearch

τ^τ-Bench: An Environment for End-To-End, Realistic Agent Construction

New τ^τ-bench tasks coding agents with building deployable customer-service agents; best config, Claude Opus 5, passes only 23.9% of simulations.

Researchers introduce τ^τ-bench, an end-to-end benchmark where a developer agent must build a complete customer-service agent from real business records, a client with requirements, a production API, an inherited codebase, and cost/model limits, then is scored by deploying it against held-out simulated users. Across 53 tasks in four domains, the strongest configuration, Claude Opus 5 under Claude Code, passes just 23.9% of evaluation simulations versus an 82.2% expert-authored reference ceiling. Failure modes mirror those of human developers: shallow queries instead of deep record comprehension, almost no client communication, and shipping the first architecture that runs rather than experimenting.

Hugging Face daily papers · 12d agoAI research

Verifiable by Construction: Claim-Level Evaluation of Verbatim Citation in Clinical Question Answering

Evaluation of twelve LLMs on 222 clinical questions shows verbatim quotes rarely substantiate claims; claude-opus-5 fully substantiates only 37.1%.

The authors build a standardized harness over four clinical practice guidelines and evaluate twelve LLMs on 222 synthetic clinical questions, measuring citation attachment, verbatim quote production, and claim substantiation. Most models attach verbatim quotes to over 90% of claims from prompting alone, though lightweight models like claude-haiku-4.5 struggle. Quotes frequently fail to substantiate claims: claude-opus-5 quotes 98.0% of claims but fully substantiates only 37.1%, exposing a capability gap for verifiable clinical QA.

arXiv cs.AI / cs.LG / cs.CL · 1d agoAI research

CenterPoint Energy Confirms Data Breach Exposing Customers’ Personal Information

CenterPoint Energy confirmed an unauthorized third party accessed customer personal data via an external system, disclosed in an SEC Form 8-K filing.

CenterPoint Energy disclosed in a September 14, 2026 Form 8-K that an unauthorized third party obtained personal information of some customers through one of the company's external systems. The company learned of the incident after an online post claimed possession of a customer dataset, then activated incident-response protocols and engaged external forensic specialists. Electric and gas delivery operations were unaffected and the company does not expect a material financial impact, though response, notification, and compliance costs are being incurred. The number of affected customers, data types, and threat actor remain undisclosed as the investigation continues.

GBHackers · 2h agoData breach 4 sources

Lner Supply Chain Attack Customer

LNER reportedly suffered a supply chain cyberattack affecting customer data, according to the Infosecurity Magazine headline.

The Infosecurity Magazine headline indicates a supply chain attack affected UK rail operator London North Eastern Railway (LNER) and its customers. No article text was available, so the scope, data types and third party involved are unconfirmed.

Infosecurity Magazine · Aug 16, 2026Data breach

How Zapier transformed core marketing processes with ChatGPT Work

Zapier's enterprise marketing team uses ChatGPT Work to cut lead-funnel drop-offs and automate reporting.

OpenAI published a customer story on how Zapier's enterprise marketing team adopted ChatGPT Work. Use cases include reducing lead funnel drop-offs, building campaign assets, and automating reporting. This is marketing case-study content rather than a product or research announcement.

OpenAI News · Aug 10, 2026AI industry

Trezor Supply Chain Breach Now Impacts 81,000 Customers

Trezor says a breach at shipping partner ShipMonk exposed data of 81,000 customers, 67,000 more than first reported, including orders back to 2019.

Trezor's September 4 update revealed that stolen ShipMonk data also included order data from November 2019 to August 2021, expanding the incident beyond the May 10 to August 8, 2026 window disclosed on August 13, and raising affected customers to 81,000, a 479% increase over the original estimate. Exposed fields include names, emails, phone numbers, shipping addresses, and order numbers; no wallet credentials or recovery seed data were reported stolen. Trezor blamed ShipMonk for retaining data despite repeated written deletion assurances, is considering legal action, and warned customers of heightened phishing, scam calls, and physical security risks.

Infosecurity Magazine · 8d agoData breach1

Understanding Operator Attitudes Toward AI-Supported Decision Making in Maritime Operations

A survey of maritime professionals finds positive but scenario-sensitive attitudes toward AI collision-avoidance assistants, urging design for calibrated reliance.

The study surveyed maritime stakeholders on attitudes toward AI-supported collision-avoidance assistants for Maritime Autonomous Surface Ships, measuring technology anxiety, trust in automation, and explanation quality with established questionnaires plus thematic analysis of open responses. Results show generally positive disposition, no clear age-related openness differences, stable trust across scenarios, and multidimensional, scenario-sensitive explanation ratings. Participants valued decision support and situation awareness but worried about AI reliability, over-reliance, and skill loss; the authors recommend designing for calibrated reliance with domain experts in the loop rather than maximizing automation or trust.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research1

Virgin Atlantic sharpens customer journeys with ChatGPT Work

Virgin Atlantic uses ChatGPT Work to accelerate research, planning, and customer-journey decisions.

OpenAI published a customer story on Virgin Atlantic adopting ChatGPT Work. The airline uses it to accelerate research, product planning, and decision-making, and to connect signals across the customer journey. This is promotional case-study content.

OpenAI News · Aug 10, 2026AI industry

What the 3M ChatGPT case reveals about AI governance

3M litigation shows ChatGPT prompts can become discoverable evidence, forcing enterprises to govern AI conversation records.

In the Watson Grinding explosion litigation, an engineering expert retained by 3M had used ChatGPT, and a surfaced prompt asked the system to 'show how 3M is 0% at fault'; after an off-record deposition demand, more than 350 pages of previously unproduced ChatGPT material were provided. The author argues AI interaction histories are becoming part of decision records and discovery material, a trend the American Bar Association has already examined. Enterprises are urged to manage retention, ownership, sharing, and deletion of AI conversation logs across tools like ChatGPT, Copilot, Claude, and Gemini.

CSO Online · 2d agoPolicy & legal

Hackers Expose Data of 1.2 Million Heights Finance Customers

Heights Finance is notifying over 1.2 million customers that hackers accessed a third-party cloud platform holding contact, bank and government ID data.

Heights Finance, a U.S. consumer lender, discovered unauthorized access on May 7, 2026 to a third-party cloud platform used to store customer data; its internal loan management systems and operations were not affected. Exposed data varies by person and may include contact details, financial and bank account information, government IDs and dates of birth for customers, loan applicants, inquirers, and former borrowers of Curo Management and related brands. The company is offering 24 months of free credit monitoring and identity protection; dark web monitoring found no evidence of publication and no threat actor has claimed responsibility.

Security Affairs · 28d agoData breach in the wild

Emergency Department Revisit Quality Review Screening: Exploring Human Decision-Making and Artificial Intelligence Support

A retrospective study found GPT-4 over-flagged emergency department revisit cases while an LLM knowledge-graph screener achieved 83-100% positive predictive value.

In an exploratory retrospective study of 99 emergency department diagnosis pairs from a multihospital health system, clinicians and GPT-4 independently judged whether revisit pairs warranted further assessment. GPT-4 responses correlated poorly with clinicians, flagging 94% of pairs for follow-up, 4.4-13.3 times more than clinicians, though prompt engineering was minimal. An algorithm leveraging an LLM-populated knowledge graph (KGA) achieved 83-100% positive predictive value against at least one clinician rater, suggesting LLM-based screening could broaden revisit quality review without substantially increasing reviewer workload.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research1

ActReview: Rebuttal-Guided Training Data and Rubric Rewards for Actionable Peer Review Generation

ActReview post-trains Qwen3-8B-Base on OpenReview rebuttals to generate actionable peer-review feedback with grounded revision suggestions, benchmarked on 1,000 curated instances.

The paper defines Actionable Peer-review Generation as diagnostic claim generation plus revision suggestion generation and introduces ActReview, a rebuttal-guided post-training framework. From OpenReview review-rebuttal threads the authors build ActReview-40K, aligning reviewer weaknesses with author responses grounded in localized paper evidence, and post-train Qwen3-8B-Base with multi-task SFT followed by GRPO using weakness-specific rubric rewards. They also release ActReview-Bench, a human-curated 1,000-instance benchmark, on which ActReview outperforms prior specialized review-generation models on actionability and grounding while remaining competitive with strong prompt-based LLMs. Human evaluation confirms improved revision usefulness but identifies a remaining gap in technical accuracy.

Hugging Face daily papers · 8d agoAI research

Distill Globally, Adapt Locally: Reasoning Distillation and Product-Type Test-Time Training for Scalable Trade-Up Recommendation

A distillation framework compresses LLM reasoning into a 15.5M-parameter trade-up recommendation model reaching AUC 0.941 with product-type test-time training.

The paper targets trade-up recommendation, which identifies higher-quality alternatives that preserve customer purchase intent. A retrieval-augmented few-shot LLM teacher generates labels and rationales that supervise a compact embedding-pair classifier; at inference the 15.5M-parameter student uses only two precomputed 768-dimensional embeddings with no LLM calls. On 8,352 annotated pairs, label-only training scored AUC 0.912, reasoning distillation reached 0.924, and product-type test-time training lifted it to 0.941 with average precision 0.940. The distilled student is roughly 5,000x faster and 10,000x cheaper than direct LLM inference on a 100K-pair proxy catalog.

arXiv cs.AI / cs.LG / cs.CL · 11d agoAI research

How Virginia Tech Connected Pentesting to Its Engineering Workflow

Horizon3.ai customer story details Virginia Tech automating external pentesting via NodeZero's GraphQL API with GitLab and ServiceNow integration for remediation tracking.

Horizon3.ai published a customer story describing how Virginia Tech, whose environment serves more than 38,000 students across hundreds of independent departments and multiple cloud providers, used NodeZero's GraphQL API to automate external pentesting through GitLab. Findings are routed directly into ServiceNow for subnet-owner assignment and remediation tracking, creating a repeatable attack-validation-to-remediation workflow.

Horizon3.ai · 12d agoIndustry1

Recorded Future Launches Digital Risk Protection, Unifying Brand and Identity Monitoring

Recorded Future launched Digital Risk Protection, unifying brand and identity monitoring across five external threat surfaces in one workflow.

Recorded Future announced Digital Risk Protection, combining brand threat monitoring and identity exposure monitoring across five use cases: malicious site, impersonation, code repository, dark web brand, and identity exposure monitoring. The platform includes an AI Triage Agent that automates alert evaluation with explicit verdicts and context, expanding social media analysis, OCR, full Telegram coverage, and infostealer log ingestion. Gartner's 2026 Magic Quadrant folded digital risk protection into cyber threat intelligence technologies, and the launch cites $15.9 billion in 2025 US fraud/scam losses, up 28% year over year.

Recorded Future · 7d agoTools

From Reweighting to Rewriting: Unlocking the Intervention Effects of Influential Samples in Training Data Attribution

Study shows rewriting responses of influence-selected training examples shifts LLM behavior more strongly than reweighting the same samples.

The paper examines training data attribution, arguing that influence functions identify high-leverage examples whose value goes unrealized under conventional weight-based reweighting interventions. It introduces influence-guided response rewriting, which replaces the responses of influence-selected examples with behavior-aligned or behavior-opposed supervision while keeping instructions fixed, tested across four open-weight LLMs using epistemic abstention as the primary testbed. Rewriting produces stronger, more persistent, and bidirectional behavioral shifts, including on safety refusal, while reweighting the same examples yields weak, inconsistent effects. The results motivate intervention-aware evaluation of TDA methods.

Hugging Face daily papers · 14d agoAI research

Logistics Giant Ceva Suffers Data Breach Impacting European Clients

Ceva Logistics suffers a supply chain attack and data breach with a large blast radius impacting European clients.

Ceva Logistics, a major global logistics provider, suffered a data breach impacting its European clients. The incident appears to be a supply chain attack with a large potential blast radius affecting downstream customers. Details on compromised data volumes and the initial intrusion vector remain limited.

Infosecurity Magazine · Aug 11, 2026Data breach

Necessary or Sufficient? Evaluating LLM Explanations With Behavioural Evidence

New framework tests whether LLM-cited explanation factors are necessary or sufficient, finding weak correlation across Claude, GPT, and Gemini models.

An arXiv paper introduces black-box intervention tests measuring whether factors LLMs cite in their explanations are necessary or sufficient for their outputs in agent oversight workflows. Across eight models from the Claude, GPT, and Gemini families, Spearman correlations between cited rankings and measured influence ranged from 0.349-0.354 (advisor recommendation) to 0.431-0.580 (prompt monitoring). Uncited factors scored above the lowest cited factor in up to 57.6% of advisor responses, showing cited top-three factors do not reliably identify the most influential inputs.

Involving before Evolving: A Vision for Trustworthy Enterprise Digital Twin Engineering

Vision paper proposes 'involving before evolving' staged approach for trustworthy enterprise digital twins, validated via an ongoing Michelin prototype.

The paper presents a three-stage vision for enterprise digital twin (EDT) engineering that prioritizes early organizational buy-in before evolving toward federation and full interoperability. The approach combines foundation models for rapid prototyping, an ontological backbone for federated interoperability, and observability tooling to build stakeholder trust. The vision is grounded in an ongoing collaboration with Michelin, where an initial working prototype helped secure stakeholder buy-in.

arXiv cs.AI / cs.LG / cs.CL · 4d agoAI research

Why User Studies and Participant Experience Reporting Matter for VR Motion Privacy?

User studies explain VR motion privacy mechanism acceptance far better than physical deviation metrics, a study of three mechanisms finds.

The paper examines how well physical deviation predicts user acceptance of VR motion privacy mechanisms compared to user studies, testing three mechanisms at five deviation levels. User studies explain substantially more variation in mechanism acceptance, though physical deviation remains significant, and prior VR experience affects acceptance. Public VR game leaderboards expose motion recordings from hundreds of thousands of users, creating identification and profiling risks. The authors recommend combining physical deviation metrics with user studies and reporting participants' prior experience.

arXiv cs.CR · 5d agoResearch

Trezor data breach impact now reaches 81,000 customers

Trezor's ShipMonk breach now affects 81,000 customers, adding 67,000 US customers after Metabase exploitation by ShinyHunters-linked attackers.

Trezor expanded its August 13 breach disclosure, saying the incident at shipping partner ShipMonk now affects 81,000 customers, with 67,000 additional US customers who ordered between November 2019 and August 2021 exposed. Attackers exploited a Metabase SQL injection zero-day to access ShipMonk's systems, exposing names, emails, phone numbers, shipping addresses, and order numbers; ShipMonk reportedly received extortion emails from the ShinyHunters gang. Trezor's own systems and devices were not compromised, and affected users are warned of phishing and scams. The broader Metabase campaign also hit Tally and Framework.

BleepingComputer · 9d agoData breach in the wild