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ESSAM: A Novel Competitive Evolution Strategies Approach to Reinforcement Learning for Memory Efficient LLMs Fine-Tuning

arXiv:2602.01003v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a key training step for improving mathematical reasoning in large language models (LLMs), but it often

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Evaluating Large Language Models in Scientific Discovery

DGX agent

arXiv:2512.15567v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and

model-releasesarxiv-cs-ai

11 May 2026

Evaluating Prompt Injection Defenses for Educational LLM Tutors: Security-Usability-Latency Trade-offs

arXiv:2605.06669v1 Announce Type: cross Abstract: Educational LLM tutors face a core AI alignment challenge: they must follow user intent while preserving pedagogical constraints and safety policies.

Ever wished your agent could read PDFs, images, and Office documents as easily as plain text? Or combine the safety of a secure sandbox with…

model-releasesjerry-liu--x

Ever wished your agent could read PDFs, images, and Office documents as easily as plain text? Or combine the safety of a secure sandbox with the full power of Bash access? We built exactly that. Meet

Exact Flow Linear Attention: Exact Solution from Continuous-Time Dynamics

arXiv:2512.12602v4 Announce Type: replace Abstract: In this paper, we introduce Exact Flow Linear Attention~(EFLA), an exact-flow formulation of delta-rule linear attention. We show that the delta-rul

Exact Is Easier: Credit Assignment for Cooperative LLM Agents

arXiv:2603.06859v2 Announce Type: replace-cross Abstract: Removing an agent from a cooperative team to measure its contribution seems natural, yet in multi-agent LLM systems this evaluation distorts t

Excluding the Target Domain Improves Extrapolation: Deconfounded Hierarchical Physics Constraints

arXiv:2605.07485v1 Announce Type: cross Abstract: Extrapolation to out-of-distribution conditions is a fundamental challenge for physics-constrained deep generative models. Existing methods apply phys

FactoryBench: Evaluating Industrial Machine Understanding

arXiv:2605.07675v1 Announce Type: new Abstract: We introduce FactoryBench, a benchmark for evaluating time-series models and LLMs on machine understanding over industrial robotic telemetry. Q&A pairs

Falcon 9 is vertical at pad 40 in Florida ahead of tomorrow’s launch of Dragon’s 34th Commercial Resupply Services mission to the @Space_Sta…

model-releaseselon-musk--x

Falcon 9 is vertical at pad 40 in Florida ahead of tomorrow’s launch of Dragon’s 34th Commercial Resupply Services mission to the @Space_Station. Teams are keeping an eye on weather, which is currentl

FAME: Forecasting Academic Impact via Continuous-Time Manifold Evolution

arXiv:2605.07208v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to brainstorm and evaluate research ideas, yet assessing such judgments is fundamentally difficult be

FANoS-v2: Feedback-Controlled Momentum with Thermostat Damping for Lightweight Neural Optimization

arXiv:2601.00889v2 Announce Type: replace Abstract: FANOS{} is a PyTorch optimizer that augments RMS-preconditioned momentum with a scalar feedback controller over update energy. The public reference

Fast Byte Latent Transformer

arXiv:2605.08044v1 Announce Type: cross Abstract: Recent byte-level language models (LMs) match the performance of token-level models without relying on subword vocabularies, yet their utility is limi

FastOmniTMAE: Parallel Clause Learning for Scalable and Hardware-Efficient Tsetlin Embeddings

arXiv:2605.06982v1 Announce Type: new Abstract: Embedding models in natural language processing (NLP) increasingly rely on deep architectures such as BERT, while simpler models such as Word2Vec provid

Fidel-TS: A High-Fidelity Multimodal Benchmark for Time Series Forecasting

arXiv:2509.24789v4 Announce Type: replace Abstract: The evaluation of time series forecasting models is hindered by a lack of high-quality benchmarks, leading to overestimated assessments of progress.

Fine-tuning a vision-language model for fracture-surface morphology recognition

arXiv:2605.07145v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong potential for scientific image understanding, but general-purpose models often lack the domain-specifi

Fine-tuning on your proprietary data is the highest leverage thing you can do. Prompts get copied overnight. A model trained on your data, y…

model-releasesfireworks-ai--x

Fine-tuning on your proprietary data is the highest leverage thing you can do. Prompts get copied overnight. A model trained on your data, your evals, your edge cases is a strong moat. OpenAI is windi

FinReasoning: A Hierarchical Benchmark for Reliable Financial Research Reporting

model-releasesarxiv-cs-cl

arXiv:2603.19254v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in financial research workflows, where their role is evolving from single-model assistance fo

Flat Channels to Infinity in Neural Loss Landscapes

arXiv:2506.14951v4 Announce Type: replace-cross Abstract: The loss landscapes of neural networks contain minima and saddle points that may be connected in flat regions or appear in isolation. We ident

Frequency-Aware Model Parameter Explorer: A new attribution method for improving explainability

arXiv:2510.03245v2 Announce Type: replace-cross Abstract: State-of-the-art attribution methods rely on adversarial sample generation that applies an all-pass filter across the frequency spectrum, disc

From Clouds to Hallucinations: Atmospheric Retrieval Hijacking in Remote Sensing Vision-Language RAG

arXiv:2605.07273v1 Announce Type: cross Abstract: Multimodal RAG systems increasingly rely on vision-language retrievers to ground visual queries in external textual evidence. Existing adversarial stu

From Pixels to Prompts: Vision-Language Models

arXiv:2605.07544v1 Announce Type: new Abstract: When you read a paper about a new Vision-Language Model today, it can be easy to forget how strange this idea would have sounded not so long ago. Teachi

From Synthetic to Real: Toward Identity-Consistent Makeup Transfer with Synthetic and Real Data

arXiv:2605.07861v1 Announce Type: new Abstract: Makeup transfer aims to apply the makeup style of a reference portrait to a source portrait while preserving identity and background. Early methods form

GAD in the Wild: Benchmarking Graph Anomaly Detection under Realistic Deployment Challenges

arXiv:2605.07133v1 Announce Type: cross Abstract: Graph Anomaly Detection (GAD) is a critical task in graph machine learning with vital applications in financial fraud detection and social platform go

Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning

arXiv:2605.06734v1 Announce Type: cross Abstract: Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states. Quantum FWPs (

GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning

arXiv:2605.07817v1 Announce Type: cross Abstract: Human visual reasoning is governed by active vision, a process where metacognitive control drives top-down goal-directed attention, dynamically routin

GC-ART: Global Learnable Second-Order Rational Tone Curves for Illumination Robustness

arXiv:2605.07329v1 Announce Type: new Abstract: We introduce GC-ART (Global Curve Adaptive Rational Tone-mapping), a lightweight differentiable pre-processing module for robust image classification. G

Generalized Euler Logarithm and its Applications in Machine Learning: Natural Gradient, Backpropagation, Generalized EG, Mirror Descent and OLPS

arXiv:2502.17500v3 Announce Type: replace-cross Abstract: This paper investigates in depth the fundamental properties of the two-parameter generalized Euler logarithm and its inverse, the associated d

GLiGuard: Schema-Conditioned Classification for LLM Safeguard

model-releasesarxiv-cs-cl

arXiv:2605.07982v1 Announce Type: new Abstract: Ensuring safe, policy-compliant outputs from large language models requires real-time content moderation that can scale across multiple safety dimension

Globally Optimal Training of Spiking Neural Networks via Parameter Reconstruction

arXiv:2605.08022v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have been proposed as biologically plausible and energy-efficient alternatives to conventional Artificial Neural Networ

Goal-Conditioned Decision Transformer for Multi-Goal Offline Reinforcement Learning

arXiv:2410.06347v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) in robotics faces significant hurdles regarding sample efficiency and generalization across varying goals. While O

Google says criminals used AI to build a working zero-day exploit for the first time

model-releasessiliconangle

Criminal hackers have used artificial intelligence to develop a working zero-day exploit, the first confirmed case of its kind, according to a report released today by Google LLC’s Google Threat Intel

Gradient-Based LoRA Rank Allocation Under GRPO: An Empirical Study

model-releasesarxiv-cs-cl

arXiv:2605.07366v1 Announce Type: new Abstract: Adaptive rank allocation for LoRA, allocating more parameters to important layers and fewer to unimportant ones, consistently improves efficiency under

Gradient Extrapolation-Based Policy Optimization

arXiv:2605.06755v1 Announce Type: cross Abstract: Reinforcement learning is widely used to improve the reasoning ability of large language models, especially when answers can be automatically checked.

Gradient Starvation in Binary-Reward GRPO: Why Group-Mean Centering Fails and Why the Simplest Fix Works

arXiv:2605.07689v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) is a standard algorithm for reinforcement learning from verifiable rewards, but its group-mean-centered advant

Graph Representation Learning Augmented Model Manipulation on Federated Fine-Tuning of LLMs

arXiv:2605.07961v1 Announce Type: new Abstract: Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated

Graph-Structured Hyperdimensional Computing for Data-Efficient and Explainable Process-Structure-Property Prediction

arXiv:2605.07999v1 Announce Type: cross Abstract: Multiphoton photoreduction enables high-fidelity fabrication of complex 3D microstructures, yet reliable process-structure-property (PSP) prediction r

GraphReAct: Reasoning and Acting for Multi-step Graph Inference

arXiv:2605.07357v1 Announce Type: new Abstract: Reasoning-acting frameworks enhance large language models (LLMs) by interleaving reasoning with actions for dynamic information acquisition. However, ex

Grok just completely changed the game for real-time financial research. We just got the preview to 'Grok Skills,' and they look 10x more pow…

model-releaseselon-musk--x

Grok just completely changed the game for real-time financial research. We just got the preview to 'Grok Skills,' and they look 10x more powerful than Claude Skills. In seconds, you can create workflo

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations

arXiv:2605.07053v1 Announce Type: cross Abstract: Benchmarks like GSM8K are popular measures of mathematical reasoning, but leaderboard gains can overstate true capability due to memorization of fixed

GTIG AI Threat Tracker: Adversaries Leverage AI for Vulnerability Exploitation, Augmented Operations, and Initial Access

model-releasesgoogle-cloud-ai

Executive Summary Since our February 2026 report on AI-related threat activity, Google Threat Intelligence Group (GTIG) has continued to track a maturing transition from nascent AI-enabled operations

Hallucination Detection via Activations of Open-Weight Proxy Analyzers

arXiv:2605.07209v1 Announce Type: cross Abstract: We introduce a proxy-analyzer framework for detecting hallucinations in large language models. Instead of looking inside the generating model, our sys

Have Graph -- Will Lift? The Case for Higher-Order Benchmarks

arXiv:2605.07397v1 Announce Type: new Abstract: After a somewhat rocky start, geometry and topology have established a foothold in machine learning. Message passing, either on graphs or higher-order c

Head Similarity: Modeling Structured Whole-Head Appearance Beyond Face Recognition

arXiv:2605.07766v1 Announce Type: new Abstract: Many vision applications require identity consistency beyond strict biometric recognition, especially under non-frontal views or when facial cues are mi

HiDream-Studio v.01 has been released! It is fast and powerful and open-sourced on Github | Easy Install

model-releasesr-stablediffusion

HiDream-Studio v.01 was open-sourced on May 8, 2026, releasing the HiDream-O1-Image model (8B parameters) with both undistilled and distilled variants. HiDream-O1-Image is a unified image generative f

Hierarchical Dual-Subspace Decoupling for Continual Learning in Vision-Language Models

arXiv:2605.07512v1 Announce Type: new Abstract: Class-incremental learning aims to continuously acquire new knowledge while preserving previously learned information, thereby mitigating catastrophic f

Hierarchical Task Network Planning with LLM-Generated Heuristics

arXiv:2605.07707v1 Announce Type: new Abstract: HTN planning is a variation of classical planning where, instead of searching for a linear sequence of actions, an algorithm decomposes higher-level tas

How Big Should a Wireless Foundation Model Be?

arXiv:2605.07266v1 Announce Type: cross Abstract: Wireless foundation models are rapidly emerging as a key enabler of AI-native communication systems, yet a fundamental question remains unanswered: ho

How ChatGPT adoption broadened in early 2026

In early 2026, ChatGPT expanded its user base across broader demographics and industry sectors, moving beyond early adopters to mainstream adoption. The report likely documents growth metrics, new use

model-releasesopenai