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Beyond Social Pressure: Benchmarking Epistemic Attack in Large Language Models

arXiv:2604.07749v1 Announce Type: new Abstract: Large language models (LLMs) can shift their answers under pressure in ways that reflect accommodation rather than reasoning. Prior work on sycophancy h

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Model Releases

Beyond Surface Artifacts: Capturing Shared Latent Forgery Knowledge Across Modalities

DGX agent

arXiv:2604.07763v1 Announce Type: new Abstract: As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existi

model-releasesarxiv-cs-cv

10 Apr 2026

BiScale-GTR: Fragment-Aware Graph Transformers for Multi-Scale Molecular Representation Learning

arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN

Blending Human and LLM Expertise to Detect Hallucinations and Omissions in Mental Health Chatbot Responses

arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet

Blind Refusal: Language Models Refuse to Help Users Evade Unjust, Absurd, and Illegitimate Rules

arXiv:2604.06233v1 Announce Type: new Abstract: Safety-trained language models routinely refuse requests for help circumventing rules. But not all rules deserve compliance. When users ask for help eva

Bootstrapping Sign Language Annotations with Sign Language Models

arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain

Break Me If You Can: Self-Jailbreaking of Aligned LLMs via Lexical Insertion Prompting

arXiv:2601.02670v2 Announce Type: replace Abstract: We introduce self-jailbreaking, a threat model in which an aligned LLM guides its own compromise. Unlike most jailbreak techniques, which oft

BREAKING: GLM 5.1 by @Zai_org overwhelmingly dominates design-centric coding tasks amongst open-weight models In the categories featured bel…

model-releaseszhipu-ai--x

BREAKING: GLM 5.1 by @Zai_org overwhelmingly dominates design-centric coding tasks amongst open-weight models In the categories featured below, it is most comparable to Opus 4.6 by @AnthropicAI at ~1/

Bridging Theory and Practice in Crafting Robust Spiking Reservoirs

arXiv:2604.06395v1 Announce Type: new Abstract: Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos

Broken by Default: A Formal Verification Study of Security Vulnerabilities in AI-Generated Code

arXiv:2604.05292v2 Announce Type: replace-cross Abstract: AI coding assistants are now used to generate production code in security-sensitive domains, yet the exploitability of their outputs remains u

BTC-LLM: Efficient Sub-1-Bit LLM Quantization via Learnable Transformation and Binary Codebook

arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.

CADENCE: Context-Adaptive Depth Estimation for Navigation and Computational Efficiency

arXiv:2604.07286v1 Announce Type: cross Abstract: Autonomous vehicles deployed in remote environments typically rely on embedded processors, compact batteries, and lightweight sensors. These hardware

Calibration of a neural network ocean closure for improved mean state and variability

arXiv:2604.06398v1 Announce Type: cross Abstract: Global ocean models exhibit biases in the mean state and variability, particularly at coarse resolution, where mesoscale eddies are unresolved. To add

CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data

arXiv:2604.07583v1 Announce Type: new Abstract: Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performanc

CAMotion: A High-Quality Benchmark for Camouflaged Moving Object Detection in the Wild

arXiv:2604.08287v1 Announce Type: new Abstract: Discovering camouflaged objects is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings.

Can Vision Language Models Judge Action Quality? An Empirical Evaluation

arXiv:2604.08294v1 Announce Type: cross Abstract: Action Quality Assessment (AQA) has broad applications in physical therapy, sports coaching, and competitive judging. Although Vision Language Models

CASE: Cadence-Aware Set Encoding for Large-Scale Next Basket Repurchase Recommendation

arXiv:2604.06718v2 Announce Type: cross Abstract: Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a

Chunks as Arms: Multi-Armed Bandit-Guided Sampling for Long-Context LLM Preference Optimization

arXiv:2508.13993v2 Announce Type: replace Abstract: Long-context modeling is critical for a wide range of real-world tasks, including long-context question answering, summarization, and complex reason

Claude for Word is now in beta. Draft, edit, and revise documents directly from the sidebar. Claude preserves your formatting, and edits app…

model-releasesboris-cherny--x

Claude for Word is now in beta. Draft, edit, and revise documents directly from the sidebar. Claude preserves your formatting, and edits appear as tracked changes. Available on Team and Enterprise pla

Claude now supports dynamic looping. If you run /loop without passing an interval, Claude will dynamically schedule the next tick based on y…

model-releasesboris-cherny--x

Claude now supports dynamic looping. If you run /loop without passing an interval, Claude will dynamically schedule the next tick based on your task. It also may directly use the Monitor tool to bypas

ClawBench: Can AI Agents Complete Everyday Online Tasks?

arXiv:2604.08523v1 Announce Type: new Abstract: AI agents may be able to automate your inbox, but can they automate other routine aspects of your life? Everyday online tasks offer a realistic yet unso

ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces

arXiv:2604.05172v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evalu

Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding

arXiv:2603.18472v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains u

Commander-GPT: Dividing and Routing for Multimodal Sarcasm Detection

arXiv:2506.19420v2 Announce Type: replace Abstract: Multimodal sarcasm understanding is a high-order cognitive task. Although large language models (LLMs) have shown impressive performance on many dow

Consistency-Guided Decoding with Proof-Driven Disambiguation for Three-Way Logical Question Answering

arXiv:2604.06196v1 Announce Type: cross Abstract: Three-way logical question answering (QA) assigns True/False/Unknown to a hypothesis H given a premise set S. While modern large language models

ConsistRM: Improving Generative Reward Models via Consistency-Aware Self-Training

arXiv:2604.07484v1 Announce Type: cross Abstract: Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering grea

Contextual Earnings-22: A Speech Recognition Benchmark with Custom Vocabulary in the Wild

arXiv:2604.07354v1 Announce Type: new Abstract: The accuracy frontier of speech-to-text systems has plateaued on academic benchmarks.1 In contrast, industrial benchmarks and adoption in high-stakes do

Continual Visual Anomaly Detection on the Edge: Benchmark and Efficient Solutions

arXiv:2604.06435v1 Announce Type: cross Abstract: Visual Anomaly Detection (VAD) is a critical task for many applications including industrial inspection and healthcare. While VAD has been extensively

ConvoLearn: A Dataset for Fine-Tuning Dialogic AI Tutors

arXiv:2601.08950v3 Announce Type: replace Abstract: Despite their growing adoption in education, LLMs remain misaligned with the core principle of effective tutoring: the dialogic construction of know

CoreWeave inks multiyear cloud deal with Anthropic

model-releasessiliconangle

CoreWeave Inc. today announced that it has won a multiyear contract to supply Anthropic PBC with cloud infrastructure. The company’s shares closed 11% higher on the news. The data center capacity comm

CrashSight: A Phase-Aware, Infrastructure-Centric Video Benchmark for Traffic Crash Scene Understanding and Reasoning

arXiv:2604.08457v1 Announce Type: new Abstract: Cooperative autonomous driving requires traffic scene understanding from both vehicle and infrastructure perspectives. While vision-language models (VLM

Create Expert Content: Local Testing of a Multi-Agent System with Memory

model-releasesgoogle-cloud-ai

In support of our mission to accelerate the developer journey on Google Cloud, we built Dev Signal: a multi-agent system designed to transform raw community signals into reliable technical guidance by

Cron Jobs — AI That Works on a Schedule Tell Qwen Code 'check if tests pass every 30 minutes' and it sets up a cron job in your session. No …

Cron Jobs — AI That Works on a Schedule Tell Qwen Code 'check if tests pass every 30 minutes' and it sets up a cron job in your session. No crontab editing, no scripts to write. Use /loop commend. Wor

model-releasesqwen--x

Cross-Lingual Transfer and Parameter-Efficient Adaptation in the Turkic Language Family: A Theoretical Framework for Low-Resource Language Models

arXiv:2604.06202v1 Announce Type: cross Abstract: Large language models (LLMs) have transformed natural language processing, yet their capabilities remain uneven across languages. Most multilingual mo

CryoSplat: Gaussian Splatting for Cryo-EM Homogeneous Reconstruction

arXiv:2508.04929v4 Announce Type: replace-cross Abstract: As a critical modality for structural biology, cryogenic electron microscopy (cryo-EM) facilitates the determination of macromolecular structu

CycleChart: A Unified Consistency-Based Learning Framework for Bidirectional Chart Understanding and Generation

arXiv:2512.19173v2 Announce Type: replace Abstract: Current chart-related tasks, such as chart generation (NL2Chart), chart schema parsing, chart data parsing, and chart question answering (ChartQA),

DDP-SA: Scalable Privacy-Preserving Federated Learning via Distributed Differential Privacy and Secure Aggregation

arXiv:2604.07125v1 Announce Type: cross Abstract: This article presents DDP-SA, a scalable privacy-preserving federated learning framework that jointly leverages client-side local differential privacy

Dear MAGA, Just out of curiosity: If president Biden had banged porn stars, cheated on multiple wives, lied 30,000 times, singlehandedly and…

model-releasesyann-lecun--x

Dear MAGA, Just out of curiosity: If president Biden had banged porn stars, cheated on multiple wives, lied 30,000 times, singlehandedly and unilaterally started a war, released 5,000 Talibanis, bombe

Detecting HIV-Related Stigma in Clinical Narratives Using Large Language Models

arXiv:2604.07717v1 Announce Type: new Abstract: Human immunodeficiency virus (HIV)-related stigma is a critical psychosocial determinant of health for people living with HIV (PLWH), influencing mental

Diagnosing and Mitigating Sycophancy and Skepticism in LLM Causal Judgment

arXiv:2601.08258v3 Announce Type: replace Abstract: Large language models increasingly fail in a way that scalar accuracy cannot diagnose: they produce a sound reasoning trace and then abandon it unde

Digital Skin, Digital Bias: Uncovering Tone-Based Biases in LLMs and Emoji Embeddings

arXiv:2604.06863v1 Announce Type: cross Abstract: Skin-toned emojis are crucial for fostering personal identity and social inclusion in online communication. As AI models, particularly Large Language

Direct Segmentation without Logits Optimization for Training-Free Open-Vocabulary Semantic Segmentation

arXiv:2604.07723v1 Announce Type: new Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment arbitrary category regions in images using open-vocabulary prompts, necessitating that exis

DISSECT: Diagnosing Where Vision Ends and Language Priors Begin in Scientific VLMs

arXiv:2604.06250v1 Announce Type: cross Abstract: When asked to describe a molecular diagram, a Vision-Language Model correctly identifies ``a benzene ring with an -OH group.'' When asked to reason ab

Distributed Interpretability and Control for Large Language Models

arXiv:2604.06483v1 Announce Type: cross Abstract: Large language models that require multiple GPU cards to host are usually the most capable models. It is necessary to understand and steer these model

Distributed Multi-Layer Editing for Rule-Level Knowledge in Large Language Models

arXiv:2604.08284v1 Announce Type: new Abstract: Large language models store not only isolated facts but also rules that support reasoning across symbolic expressions, natural language explanations, an

Do MLLMs Really Understand Space? A Mathematical Reasoning Evaluation

arXiv:2602.11635v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have achieved strong performance on perception-oriented tasks, yet their ability to perform mathematical sp

Domain-Contextualized Inference: A Computable Graph Architecture for Explicit-Domain Reasoning

arXiv:2604.04344v2 Announce Type: replace Abstract: We establish a computation-substrate-agnostic inference architecture in which domain is an explicit first-class computational parameter. This produc

Don't Overthink It: Inter-Rollout Action Agreement as a Free Adaptive-Compute Signal for LLM Agents

arXiv:2604.08369v1 Announce Type: cross Abstract: Inference-time compute scaling has emerged as a powerful technique for improving the reliability of large language model (LLM) agents, but existing me