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97770 articles
AIBullisharXiv – CS AI · May 287/10
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FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation

Researchers introduced FLUID, a production-scale recommendation system that eliminates reliance on item IDs for livestreaming platforms by using multimodal semantic codes instead. Deployed across platforms with over one billion users, the system achieves significant performance gains including 2.05% improvement in cold-start room views, addressing a fundamental challenge in recommending short-lived broadcast content.

AINeutralarXiv – CS AI · May 287/10
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CRaFT: Circuit-Guided Refusal Feature Selection via Cross-Layer Transcoders

Researchers propose CRaFT, a circuit-guided framework that identifies critical refusal features in large language models by analyzing inter-feature relationships rather than isolated activation signals. The method improves jailbreak attack success rates from 6.7% to 57.4% across benchmarks, advancing understanding of LLM safety mechanisms and highlighting vulnerabilities in model alignment.

AINeutralarXiv – CS AI · May 287/10
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Who Uses AI? Platform Selection and the Measurement of Occupational AI Exposure

Researchers demonstrate that AI exposure measurements derived from platform conversation logs significantly misrepresent actual occupational AI adoption across the workforce. The study reveals that platform-based metrics conflate AI task applicability with user demographic composition, producing estimates that vary by 90% depending on data source and can even reverse directional findings about AI's employment impact.

🧠 ChatGPT
AIBullisharXiv – CS AI · May 287/10
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SynthTools: A Framework for Scaling Synthetic Tools for Agent Development

SynthTools introduces an LLM-based pipeline for generating synthetic tool environments at scale, creating a dataset of 73,883 validated tools across 6,800 environments and 79,925 verifiable tasks. The framework demonstrates that agents trained on synthetic tool-use data can transfer capabilities to real APIs, addressing a critical bottleneck in agentic AI system development.

AIBearisharXiv – CS AI · May 287/10
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Deepfake-Eval-2024: A Multi-Modal In-the-Wild Benchmark of Deepfakes Circulated in 2024

Researchers introduce Deepfake-Eval-2024, a new benchmark dataset of real-world deepfakes collected from social media in 2024, revealing that state-of-the-art detection models experience dramatic performance drops of 45-50% compared to academic benchmarks. The findings underscore a critical gap between laboratory-validated deepfake detectors and their effectiveness against actual manipulated content in circulation.

AIBullisharXiv – CS AI · May 287/10
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The Shape of Reasoning: Topological Analysis of Reasoning Traces in Large Language Models

Researchers introduce a topological data analysis framework to evaluate reasoning quality in large language models, moving beyond traditional graph-based metrics. The study demonstrates that higher-dimensional geometric structures predict reasoning quality more effectively than standard connectivity measures, offering a practical signal for training optimization.

AIBullisharXiv – CS AI · May 287/10
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Reverse Probing: Supervised Token-level Uncertainty Quantification for Large Language Models in Clinical Text

Researchers introduce Reverse Probing, a novel uncertainty quantification framework designed specifically for clinical LLMs that estimates token-level confidence directly from existing summaries rather than sampling new outputs. The method achieves significant performance improvements on clinical datasets while reducing computational costs, advancing the critical goal of making AI systems safer for healthcare applications.

AIBullisharXiv – CS AI · May 287/10
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Deep Learning Strain Estimation: Is Physics-Based Simulation the Solution?

Researchers propose a novel physics-based simulation strategy for training deep learning models to estimate myocardial strain from echocardiography videos, achieving superior accuracy to clinical standards. The method incorporates real speckle decorrelation patterns and iterative refinement, resulting in a publicly available dataset of 1,478 synthetic videos that enables more reliable regional strain detection for cardiac diagnosis.

AIBearisharXiv – CS AI · May 287/10
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The Attentional White Bear Effect in Transformer Language Models

Researchers discovered that instruction-based suppression in transformer language models fails to eliminate prohibited concepts from internal representations, despite successfully preventing their explicit expression. The study reveals that suppressed content remains recoverable from hidden layers and continues influencing model behavior, exposing a critical gap between behavioral safety and true representational alignment.

AINeutralarXiv – CS AI · May 287/10
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Misalignment Between Backpropagation and the Hierarchy of Brain Responses to Images

Researchers using fMRI and MEG data found that while backpropagated gradients in deep neural networks can predict brain activity in higher visual cortex, their spatial and temporal organization fundamentally diverges from how the human brain processes visual information. This suggests that although artificial and biological neural networks may learn similar representations, they employ distinctly different learning mechanisms.

AIBearisharXiv – CS AI · May 287/10
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Position: Retire the "Positive Backdoor" Label -- Secret Alignment Requires Strict and Systematic Evaluation

A research position paper argues the AI/ML community should abandon the "positive backdoor" terminology and instead rigorously evaluate trigger-activated hidden behaviors as "Secret Alignment." Researchers found that existing implementations show significant brittleness in security properties, particularly in confidentiality, integrity, and availability—revealing that protective claims lack standardized evaluation frameworks.

AIBullisharXiv – CS AI · May 287/10
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OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration

Researchers introduce OmniVerifier-M1, a multimodal verification system that uses symbolic outputs like bounding boxes rather than text explanations to improve error detection in visual AI models. The approach combines meta-verification feedback with decoupled reinforcement learning to enable more reliable and interpretable verification of multimodal foundation models, with applications in autonomous error correction.

AIBullisharXiv – CS AI · May 287/10
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Where Does Toxicity Live? Mechanistic Localization and Targeted Suppression in Language Models

Researchers introduce Meow2X and TRNE, two novel frameworks that identify and suppress toxicity in large language models by localizing harmful content to specific neural layers and neurons, then neutralizing it through inference-time adjustments without retraining. The approach demonstrates consistent toxicity reduction across multiple models while preserving language quality, revealing that early MLP layers disproportionately encode toxic behavior.

AIBearisharXiv – CS AI · May 287/10
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Blind PRNG Hijacking: An Undetectable Integrity-Preserving Attack Against LLM Watermarking

Researchers have discovered SeedHijack, a supply-chain attack that compromises LLM watermarking schemes by hijacking the pseudo-random number generator (PRNG) used in watermark implementation. The attack amplifies watermark signals while remaining undetectable by current defense mechanisms, exposing a critical vulnerability in cryptographic content-provenance systems that assumed PRNG trustworthiness.

AIBullisharXiv – CS AI · May 287/10
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Text-Only Data Synthesis for Vision Language Model Training

Researchers propose a text-only framework for synthesizing vision-language model training data, eliminating the need for costly image-text pairs. The method generates two datasets (Unicorn-1.2M and Unicorn-471K-Instruction) through a three-stage process that converts text captions into synthetic visual representations, potentially reducing training costs and accelerating VLM development.

AIBullisharXiv – CS AI · May 287/10
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Knowledge Graph-Driven Expert-Level Reasoning for Neuroscience

Researchers demonstrate that knowledge graphs extracted from a single neuroscience textbook can be converted into high-quality training data to fine-tune language models, enabling expert-level reasoning that outperforms larger LLMs while using far fewer parameters. This approach challenges the prevailing assumption that domain expertise requires massive, diverse datasets, showing instead that structured, curated knowledge can produce superior specialized AI systems.

GeneralBullishCrypto Briefing · May 287/10
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Hong Kong launches gold-clearing system to become Asia’s top bullion hub

Hong Kong has launched a new gold-clearing system designed to establish itself as Asia's premier bullion trading hub. The initiative aims to enhance regional financial integration while strengthening the credibility of digital asset infrastructure in the region.

Hong Kong launches gold-clearing system to become Asia’s top bullion hub
CryptoBullishCrypto Briefing · May 287/10
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CFTC seeks to vacate $5M penalty against Gemini Trust Company

The CFTC is seeking to vacate a $5 million penalty previously imposed on Gemini Trust Company, signaling a potential shift toward more cautious regulatory enforcement in the cryptocurrency industry. This reversal suggests the agency may be reassessing its enforcement strategy and could impact how regulators approach future crypto compliance actions.

CFTC seeks to vacate $5M penalty against Gemini Trust Company
🧠 Gemini
GeneralBearishCrypto Briefing · May 28🔥 8/10
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Kuwait faces missile and drone attack amid shaky ceasefire in Iran war

Kuwait faces missile and drone attacks as tensions between Iran and regional powers escalate despite ceasefire efforts, creating geopolitical instability that threatens global energy supplies and cryptocurrency market volatility.

Kuwait faces missile and drone attack amid shaky ceasefire in Iran war
GeneralBearishCrypto Briefing · May 28🔥 8/10
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Islamic Revolutionary Guard Corps strikes US air bases across Middle East, warns of stronger retaliation

The Islamic Revolutionary Guard Corps conducted strikes on US air bases across the Middle East and warned of stronger retaliation, escalating regional tensions. This geopolitical escalation poses risks to global market stability, potentially increasing cryptocurrency volatility, energy price spikes, and heightened regulatory scrutiny on digital assets.

Islamic Revolutionary Guard Corps strikes US air bases across Middle East, warns of stronger retaliation
AI × CryptoBearishThe Block · May 287/10
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US charges Google engineer with using internal search data to pocket $1.2 million on Polymarket

A Google engineer was charged with fraud and money laundering for allegedly using confidential internal search data to make $1.2 million in profitable trades on Polymarket, a cryptocurrency prediction market. The CFTC simultaneously filed an insider trading complaint, highlighting how non-public information from tech companies can be weaponized in crypto markets.

US charges Google engineer with using internal search data to pocket $1.2 million on Polymarket
CryptoNeutralBitcoinist · May 287/10
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CFTC Reexamines Gemini Case And Asks To Erase 2025 Settlement

The CFTC has joined Gemini in requesting court relief from a 2022 judgment, indicating a significant reexamination of the regulatory case. The joint request suggests potential settlement modifications or dismissal, marking a notable shift in the enforcement action that originally targeted the cryptocurrency exchange.

CFTC Reexamines Gemini Case And Asks To Erase 2025 Settlement
🧠 Gemini
CryptoBearishNewsBTC · May 287/10
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Bitcoin Price Extends Decline Rapidly As Key Supports Collapse

Bitcoin has broken below key support levels, declining from $76,000 to trade below $75,000 with a low of $74,050. Technical indicators show bearish momentum, with the price struggling to hold above the 100-hour moving average and facing resistance at $74,850, raising concerns about potential further downside if support at $74,000 fails.

Bitcoin Price Extends Decline Rapidly As Key Supports Collapse
$BTC
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