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The vulnpocalypse rains iBugs down on Apple with record-setting number of patches

Apple's record patch cycle fixes 260+ CVEs across iOS 27 and macOS 27, including CUPS remote code execution, with no active exploitation reported.

Apple patched more than 260 CVEs across its operating systems and software, its largest single patch cycle ever, with iOS 27 fixing 122 flaws and macOS 27 Golden Gate fixing 204. Notable bugs include CVE-2026-43692, a CUPS validation issue allowing remote code execution, and CVE-2026-43689, an iOS privilege-escalation flaw granting root access. Ten CVEs were credited to AI-assisted bug hunting, including CVE-2026-65410 and CVE-2026-65409 found by Calif with Claude and Anthropic Research. None of the vulnerabilities are listed as actively exploited.

The Register · Security·Sep 15, 21:38 UTC · 1d agoVulnerabilityCVE-2026-65410CVE-2026-65409CVE-2026-43689+10 CVEs

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ZDI-26-568: Linux Kernel Net Scheduler Race Condition Local Privilege Escalation Vulnerability

ZDI disclosed a race condition (CVSS 7.5) in the Linux kernel net scheduler enabling local privilege escalation; no CVE assigned in the advisory text.

ZDI advisory ZDI-26-568 describes a race condition in the Linux kernel's net scheduler that allows local attackers to escalate privileges on affected installations. Exploitation requires the attacker to first execute high-privileged code on the target system. ZDI assigned a CVSS rating of 7.5; no CVE identifier is listed in the advisory text.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026Vulnerability

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Google Chrome 153 Released With Fixes for 42 Security Vulnerabilities

Google shipped Chrome 153 to the Stable channel fixing 42 vulnerabilities, including three critical flaws in WebGL, Internals, and Workers; no exploitation reported.

Google released Chrome 153 (153.0.8010.47/48) for Windows, macOS, and Linux, patching 42 security vulnerabilities including three rated critical: CVE-2026-91726 (out-of-bounds read in WebGL), CVE-2026-91721 (use-after-free in Internals), and CVE-2026-91749 (use-after-free in Workers). Twenty-eight fixes are rated high severity, covering use-after-free, type confusion, race condition, integer overflow, and authorization flaws across components like V8, Skia, DOM, ServiceWorker, PDF, and Extensions. Google's bulletin indicates no vulnerabilities are currently being exploited in the wild, and external researchers earned rewards up to $1,500 for reported issues. Enterprises are advised to verify fleet-wide deployment via browser-management consoles and enable automatic updates.

GBHackers·05:00 UTC · 16h agoVulnerabilityCVE-2026-91726CVE-2026-91721CVE-2026-91749+27 CVEs1

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ZDI-26-572: Linux Kernel XFRM Race Condition Local Privilege Escalation Vulnerability

ZDI publishes ZDI-26-572, a CVSS 7.5 race condition local privilege escalation in the Linux kernel's XFRM subsystem.

The Zero Day Initiative disclosed a race condition in the Linux kernel's XFRM (transform) subsystem allowing local attackers to escalate privileges. Exploitation requires the attacker to first run high-privileged code on the affected system. The advisory carries a CVSS rating of 7.5; no CVE id is listed in the disclosure text.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026Advisory

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ZDI-26-576: Linux Kernel XFRM Race Condition Local Privilege Escalation Vulnerability

ZDI disclosed a race condition local privilege escalation flaw in the Linux Kernel XFRM subsystem, CVSS 7.5, with no CVE assigned.

The Zero Day Initiative published ZDI-26-576 describing a race condition in the Linux Kernel XFRM subsystem. Local attackers can escalate privileges, but the advisory states an attacker must first be able to execute high-privileged code on the target. ZDI assigned a CVSS score of 7.5; no CVE identifier is listed in the advisory text.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026Vulnerability

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ZDI-26-686: Linux Kernel nftables Race Condition Local Privilege Escalation Vulnerability

ZDI discloses CVE-2026-74565, a CVSS 7.8 nftables race condition letting local low-privileged attackers escalate privileges on Linux.

ZDI-26-686 describes a race condition in the Linux Kernel nftables subsystem that allows local attackers to escalate privileges. Exploitation requires the ability to execute low-privileged code on the target system. ZDI assigned a CVSS rating of 7.8 and CVE-2026-74565.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoAdvisoryCVE-2026-74565

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ZDI-26-570: Linux Kernel IGMP Subsystem Race Condition Local Privilege Escalation Vulnerability

ZDI publishes ZDI-26-570, a CVSS 7.5 race condition local privilege escalation in the Linux kernel's IGMP subsystem.

The Zero Day Initiative disclosed a race condition in the Linux kernel's IGMP subsystem that allows local attackers to escalate privileges. Exploitation requires the attacker to first execute high-privileged code on the target system. ZDI assigned a CVSS rating of 7.5 to this finding; no CVE id is stated in the advisory text.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026Advisory

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ZDI-26-574: Linux Kernel Net Scheduler Connection Tracking Race Condition Local Privilege Escalation Vulnerability

A race condition (CVE-2026-46319, CVSS 7.5) in the Linux kernel net scheduler connection tracking allows local privilege escalation.

ZDI advisory ZDI-26-574 documents a race condition in the Linux kernel's net scheduler connection tracking component. Local attackers who can execute high-privileged code on a target can exploit the flaw to escalate privileges. ZDI rated the vulnerability 7.5 on CVSS and assigned CVE-2026-46319.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026VulnerabilityCVE-2026-46319

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ZDI-26-681: Linux Kernel FUSE Subsystem Race Condition Local Privilege Escalation Vulnerability

ZDI discloses CVE-2026-64265, a CVSS 7.8 race condition in the Linux Kernel FUSE subsystem enabling local privilege escalation.

ZDI-26-681 covers a race condition in the Linux Kernel FUSE subsystem that allows local attackers to escalate privileges. Exploitation requires the ability to execute low-privileged code on the target system. ZDI assigned a CVSS rating of 7.8 and CVE-2026-64265.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoAdvisoryCVE-2026-64265

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ZDI-26-688: Linux Kernel OpenvSwitch Race Condition Local Privilege Escalation Vulnerability

ZDI discloses Linux Kernel Open vSwitch race condition (CVE-2026-74465) allowing low-privileged local attackers to escalate privileges, CVSS 7.8.

ZDI-26-688 describes a race condition local privilege escalation vulnerability in the Linux Kernel's Open vSwitch implementation, tracked as CVE-2026-74465 with a CVSS rating of 7.8. An attacker must first obtain the ability to execute low-privileged code on the target system. Successful exploitation grants elevated privileges on affected installations.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2026-744651

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ZDI-26-569: Linux Kernel Net Scheduler True Link Equalizer Race Condition Local Privilege Escalation Vulnerability

ZDI publishes ZDI-26-569, a CVSS 7.5 race condition local privilege escalation in the Linux kernel net scheduler true link equalizer.

The Zero Day Initiative disclosed a race condition in the Linux kernel's net scheduler true link equalizer component enabling local privilege escalation. Exploitation requires the attacker to first run high-privileged code on the target system. The advisory carries a CVSS rating of 7.5; no CVE id is listed in the disclosure text.

ZDI Published Advisories·Aug 13, 05:00 UTC · Aug 13, 2026Advisory

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ZDI-26-693: Linux Kernel ksmbd Share Configuration Race Condition Remote Code Execution Vulnerability

ZDI-26-693: authenticated race condition in Linux kernel ksmbd share configuration allows remote code execution on ksmbd-enabled systems; CVSS 8.5.

ZDI advisory ZDI-26-693 discloses a race condition in the Linux kernel's ksmbd share configuration that allows remote attackers to execute arbitrary code on affected installations. Exploitation requires authentication, and only systems with ksmbd enabled are vulnerable. ZDI assigned a CVSS rating of 8.5; no CVE is listed in the advisory text.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerability1

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ZDI-26-689: Linux Kernel SCTP Subsystem Race Condition Information Disclosure Vulnerability

ZDI discloses Linux Kernel SCTP subsystem race condition (CVE-2026-46227) allowing low-privileged local attackers to disclose sensitive information, CVSS 6.4.

ZDI-26-689 describes a race condition information disclosure vulnerability in the Linux Kernel SCTP subsystem, assigned CVE-2026-46227 with a CVSS rating of 6.4. An attacker needs the ability to execute low-privileged code on the target system to exploit the flaw. The vulnerability exposes sensitive information from affected installations.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2026-46227

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ZDI-26-644: Oracle VirtualBox VMSVGA Race Condition Local Privilege Escalation Vulnerability

ZDI publishes ZDI-26-644 for CVE-2026-60155, a race condition local privilege escalation in Oracle VirtualBox VMSVGA, rated CVSS 7.5.

Zero Day Initiative published advisory ZDI-26-644 describing a race condition in Oracle VirtualBox's VMSVGA component. Local attackers who already execute high-privileged code on the guest system can escalate privileges on affected installations. ZDI rated the issue CVSS 7.5 and assigned CVE-2026-60155.

ZDI Published Advisories·Sep 9, 05:00 UTC · 7d agoAdvisory 6 sourcesCVE-2026-60155

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ZDI-26-684: Linux Kernel KSMBD Query Directory Request Race Condition Remote Code Execution Vulnerability

ZDI discloses CVE-2026-64397, a CVSS 9.0 unauthenticated remote code execution race condition in Linux Kernel KSMBD.

ZDI-26-684 describes a race condition in the Linux Kernel KSMBD subsystem's Query Directory Request handling that allows unauthenticated remote attackers to execute arbitrary code. Only systems with KSMBD enabled are vulnerable. ZDI assigned a CVSS rating of 9.0 and CVE-2026-64397.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoAdvisoryCVE-2026-64397

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Testing race conditions with memory access tracing and stack-based delay injection

Google Project Zero released MAccConc, Linux kernel tooling that traces memory accesses to explore and test race condition interleavings.

A Google Project Zero researcher published MAccConc (Memory Access Concurrency), tooling for exploring possible interleavings of multithreaded test cases in the Linux kernel, available on GitHub. The tools use KCOV with ASAN outline-mode instrumentation to record per-access memory traces, enabling automatic testing of all A-B-A interleavings plus terminal and GUI explorers for manual analysis. The work targets confirming race condition candidates, building reliable regression tests, and enabling concurrency fuzzing, drawing on ideas from SKI and Ned Williamson's sockfuzzer.

Google Project Zero·Sep 8, 07:00 UTC · 8d agoResearch1

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ZDI-26-685: Linux Kernel NFC NCI UART Driver Race Condition Local Privilege Escalation Vulnerability

ZDI discloses a race condition in the Linux kernel NFC NCI UART driver (CVE-2025-38416, CVSS 8.8) allowing local low-privileged attackers to escalate privileges.

ZDI advisory ZDI-26-685 covers a race condition vulnerability in the Linux kernel's NFC NCI UART driver, tracked as CVE-2025-38416 with a CVSS score of 8.8. A local attacker with the ability to execute low-privileged code can exploit the race to escalate privileges on affected systems. Exposure is limited to systems where the NFC NCI UART driver is present, and no exploitation is reported.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2025-38416

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ZDI-26-695: Linux Kernel NFSv4 Server Race Condition Remote Code Execution Vulnerability

ZDI-26-695: Linux Kernel NFSv4 server race condition (CVE-2026-89688, CVSS 8.5) enables remote code execution on nfsd systems with authentication.

ZDI advisory ZDI-26-695 describes a race condition in the Linux Kernel NFSv4 server tracked as CVE-2026-89688 with a CVSS score of 8.5. Remote attackers can execute arbitrary code, but authentication is required and only systems with nfsd enabled are vulnerable. No in-the-wild exploitation is mentioned in the advisory.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2026-896881

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ZDI-26-692: Linux Kernel eMPIA USB Device Driver Race Condition Code Execution Vulnerability

ZDI-26-692: race condition in Linux kernel eMPIA USB driver (CVE-2026-31583) lets physically present attackers execute code without authentication; CVSS 7.1.

ZDI advisory ZDI-26-692 discloses a race condition in the Linux kernel's eMPIA USB device driver that allows physically present attackers to execute arbitrary code on affected installations. Authentication is not required, but physical access to the target system is necessary. ZDI assigned a CVSS rating of 7.1 and CVE-2026-31583.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2026-31583

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ZDI-26-702: Linux Kernel usbnet Driver Race Condition Privilege Escalation Vulnerability

ZDI discloses Linux Kernel usbnet driver race condition (CVE-2025-22050) enabling physically present attackers to escalate privileges without authentication.

ZDI-26-702 covers a race condition privilege escalation vulnerability in the Linux Kernel usbnet driver, assigned CVE-2025-22050 with a CVSS rating of 7.1. A physically present attacker can escalate privileges on affected installations. Authentication is not required to exploit the vulnerability.

ZDI Published Advisories·Sep 14, 05:00 UTC · 2d agoVulnerabilityCVE-2025-22050

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Characterizing Language Generation in the Limit: Finite Witnesses and a Separation-Width Hierarch

New work characterizes language generation in the limit via finite witnesses, proves a full separation-width hierarchy, and formalizes all results in Lean.

The paper fully characterizes when language generation in the limit is possible for arbitrary families over a countable universe: each target must admit a finite positive witness such that targets activated by any finite sample share an infinite common intersection. It defines positive separation width and proves every level of the resulting hierarchy occurs, with countable families admitting singleton witnesses and unions of families with infinite common cores requiring unbounded finite witnesses. The characterization, a universal normalization, and a diagonal capture lemma are machine-checked in the Lean proof assistant, with the development maintained on GitHub.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 17:54 UTC · 7d agoAI research1

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Competence-Gated Pooling of Language Models and Priors for Event Forecasting

Paper proposes a competence gate pooling language model forecasts with external priors, improving Brier score from 0.0771 to 0.0732 across 2,357 binary questions.

The paper defines a language model's relative competence as its marginal value beyond an available external forecast, and derives conditions under Brier loss where model disagreement improves that forecast. A competence gate estimates domain-level source weights from resolved outcomes, shrinks uncertain estimates toward a global weight, and recalibrates the pooled forecast. Across 2,357 resolved binary questions and five language models, it improves the external baseline from 0.0771 to 0.0732 Brier and beats global forecast combinations, though it defers to the market on ForecastBench. Across four Qwen models, verbal confidence failed to identify when the model outperformed the external forecast, while outcome-estimated competence supported better abstention.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research

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K-Bench: a clinically calibrated benchmark for evaluating large language models in high-risk mental health conversations

Clinician-calibrated K-Bench evaluates 125 LLM configurations on 200 high-risk mental health vignettes, exposing wide variation in suicide and violence risk handling.

K-Bench is a clinician-calibrated, protected benchmark evaluating 125 model configurations from 33 base models across 14 providers on 200 multi-turn vignettes covering suicide, self-harm, domestic violence, substance misuse and no-risk presentations. A frozen GPT-4o judge achieved 94.2% exact agreement with clinician consensus across 6,751 eligible comparisons from 151 clinician-rated transcripts. Leading models combined supportive conversation with combined-risk scores above 95, while risk exploration varied substantially among weaker configurations; therapeutic prompting helped weaker models and elevated reasoning produced no average improvement. A continuously updated public leaderboard is hosted at k-bench.ai with protected test materials.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 16:49 UTC · 2d agoAI safety & security

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Molecular Déjà Vu: Digit-Level Retrieval of Published Values in Frontier Language Models

Audit of 22 frontier models finds widespread verbatim retrieval of published molecular property values, with higher reasoning increasing recall of memorized numbers.

An arXiv audit tests 22 frontier LLMs across 12 molecular regression benchmarks for verbatim retrieval of published values. More than 50% of the LLMs show verbatim retrieval on five datasets, and identical experiments are flagged 89% more often at a high reasoning level than at the lowest one. Suppressing retrieval moves model prediction errors closer together in relative terms, suggesting predictive capability is not determined solely by memorized values.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 17:32 UTC · 12d agoAI research1

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MetroLLM-Bench: Evaluating Language Models as Transit Kiosk Runtimes

MetroLLM-Bench is a 955-case benchmark testing language models as transit kiosk tool-calling runtimes across six real metro systems.

The benchmark covers 37-414-station metro systems and eleven task categories including routing, fare calculation, disruptions, accessibility, and adversarial input, with 14 deterministic and 8 semantic scoring components. Of 26 models from six vendors, a PEFT-tuned 4B Qwen 3.5 student scored 91.3 on Tier 1, exceeding GPT-5.6 (90.6/90.0), while Muse Glimmer 30B led the composite ranking. A deterministic rule-based baseline reached 84.6, and PEFT gains over base models shrank from +7.03 points at 2B to -0.91 at 27B.

Hugging Face daily papers·Sep 8, 20:00 UTC · 8d agoAI research

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Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

Researchers propose auditing LLM bias via relative hidden-state representations, detecting bias increases with 3-50x less compute than output-level benchmarks.

The paper introduces a reference-based bias auditing method that compares hidden-state representations across model variants, such as before and after fine-tuning, by encoding sentences relative to a fixed anchor set. The resulting Representational Bias Shift (Delta-B) correlates with output-level bias change in 15 of 18 tested settings, reaching |r| = 0.84 under full fine-tuning across WildGuardMix, DecodingTrust, and ToxiGen benchmarks. Thresholding Delta-B detects checkpoints whose bias increased with ROC AUC between 0.65 and 0.99 and beats a SEAT-based baseline, while auditing a model in about three minutes with 3-50x less compute.

Hugging Face daily papers·Sep 8, 20:00 UTC · 8d agoAI research1

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Type Diversity Enables Transformers to Generalise Compositionally

Researchers show lexical-versus-structural compositional generalization gaps in Transformers stem from type diversity imbalance in datasets, not architectural limits.

The paper argues that Transformers' difficulty with structural compositional generalization is an artifact of low structural type diversity in prior benchmark datasets rather than an architectural limitation. Using Grammatical Framework, the authors create linguistically diverse variants of COGS and SLOG. They find type diversity correlates with compositional generalization equally in lexical and structural test cases, contradicting previous claims that compound divergence explains task difficulty.

arXiv cs.AI / cs.LG / cs.CL·Sep 11, 17:59 UTC · 5d agoAI research

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Climate-ModernBERT: Revisiting Corpus Composition for Domain-Adaptive Continued Pretraining

Climate-ModernBERT domain-adapted encoders reach 76.3 average F1 across nine climate benchmarks, 2.8 points above vanilla ModernBERT-Base.

The authors continue pretraining ModernBERT-Base on three climate corpora - academic text, climate-filtered web data, and synthetic documents - and compare joint mixtures against parameter-space merging of specialized checkpoints. The best model achieves 76.3 average F1 across nine climate NLP benchmarks, a 2.8-point improvement over the vanilla baseline. Academic climate corpora provide the strongest adaptation signal, and parameter-space merging outperforms joint multi-source training while preserving complementary corpus information; all variants are released.

arXiv cs.AI / cs.LG / cs.CL·Sep 7, 17:41 UTC · 9d agoAI research

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LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 15:49 UTC · 12d agoAI research

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Training and Finetuning Multi-Vector Embedding Models with Sentence Transformers

Hugging Face published a tutorial on training and finetuning multi-vector embedding models using the Sentence Transformers library.

Hugging Face's blog walks through training and finetuning multi-vector embedding models with Sentence Transformers. Multi-vector approaches store multiple vectors per document to support late-interaction retrieval. The post is a practical guide for developers building retrieval pipelines with the library.

Hugging Face Blog·Aug 26, 00:00 UTC · 21d agoAI tools & infra1

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Canonical Color as a Lens into Concept Decodability in Vision Encoders and VLMs

Probing study shows vision encoders make canonical color linearly decodable from grayscale images and tie it to object identity.

Researchers use canonical color as a controlled testbed for measuring conceptual (not just visible) information in vision encoder representations. A dataset of objects with canonical colors was built, and probes on both color and grayscale images show canonical color remains decodable even when color is removed from the input, linked to predicted object identity. Extending to full VLMs, they find post-training has a surprisingly large effect on color decodability in the vision encoder.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:50 UTC · 8d agoAI research1

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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·Sep 14, 17:53 UTC · 2d agoAI research

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