Search: “papers”

Evaluating Differential Privacy Against Membership Inference in Federated Learning: Insights from the NIST Genomics Red Team Challenge

arXiv:2604.12737v1 Announce Type: cross Abstract: While Federated Learning (FL) mitigates direct data exposure, the resulting trained models remain susceptible to membership inference attacks (MIAs).

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Evaluating LLM-Generated ACSL Annotations for Formal Verification

DGX agent

arXiv:2602.13851v3 Announce Type: replace-cross Abstract: Formal specifications are crucial for building verifiable and dependable software systems, yet generating accurate and verifiable specificatio

model-releasesarxiv-cs-ai

15 Apr 2026

Hardware

Fast AI Model Partition for Split Learning over Edge Networks

arXiv:2507.01041v4 Announce Type: replace-cross Abstract: Split learning (SL) is a distributed learning paradigm that can enable computation-intensive artificial intelligence (AI) applications by part

hardwarearxiv-cs-ai

Filtered Reasoning Score: Evaluating Reasoning Quality on a Model's Most-Confident Traces

arXiv:2604.11996v1 Announce Type: cross Abstract: Should we trust Large Language Models (LLMs) with high accuracy? LLMs achieve high accuracy on reasoning benchmarks, but correctness alone does not re

Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments

arXiv:2604.12288v1 Announce Type: cross Abstract: Fine-tuning is a widely used strategy for adapting pre-trained models to new tasks, yet its methodology and theoretical properties in high-dimensional

From Plan to Action: How Well Do Agents Follow the Plan?

arXiv:2604.12147v1 Announce Type: cross Abstract: Agents aspire to eliminate the need for task-specific prompt crafting through autonomous reason-act-observe loops. Still, they are commonly instructed

Tutorials

Generating Effective CoT Traces for Mitigating Causal Hallucination

arXiv:2604.12748v1 Announce Type: new Abstract: Although large language models (LLMs) excel in complex reasoning tasks, they suffer from severe causal hallucination in event causality identification (

tutorialsarxiv-cs-cl

Generative Anonymization in Event Streams

model-releasesarxiv-cs-cv

arXiv:2604.12803v1 Announce Type: new Abstract: Neuromorphic vision sensors offer low latency and high dynamic range, but their deployment in public spaces raises severe data protection concerns. Rece

GGD-SLAM: Monocular 3DGS SLAM Powered by Generalizable Motion Model for Dynamic Environments

arXiv:2604.12837v1 Announce Type: new Abstract: Visual SLAM algorithms achieve significant improvements through the exploration of 3D Gaussian Splatting (3DGS) representations, particularly in generat

applicationsarxiv-cs-ro

Give me your ideass [N]

researchr-machinelearning

A community thread on r/MachineLearning where users are invited to share research ideas, project concepts, or suggestions related to machine learning. The '[N]' tag indicates it is a discussion post r

GTCN-G: A Residual Graph-Temporal Fusion Network for Imbalanced Intrusion Detection

arXiv:2510.07285v3 Announce Type: replace-cross Abstract: The escalating complexity of network threats and the inherent class imbalance in traffic data present formidable challenges for modern Intrusi

HiFiNet: Hierarchical Fault Identification in Wireless Sensor Networks via Edge-Based Classification and Graph Aggregation

arXiv:2511.17537v2 Announce Type: replace-cross Abstract: Wireless Sensor Networks (WSN) are the backbone of essential monitoring applications, but their deployment in unfavourable conditions increase

How Transformers Learn to Plan via Multi-Token Prediction

arXiv:2604.11912v1 Announce Type: cross Abstract: While next-token prediction (NTP) has been the standard objective for training language models, it often struggles to capture global structure in reas

IMSE: Intrinsic Mixture of Spectral Experts Fine-tuning for Test-Time Adaptation

arXiv:2603.07926v3 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) has been widely explored to prevent performance degradation when test data differ from the training distribution. H

Incentivizing High-Quality Human Annotations with Golden Questions

arXiv:2505.19134v2 Announce Type: replace-cross Abstract: Human-annotated data plays a vital role in training large language models (LLMs), such as supervised fine-tuning and human preference alignmen

safetyarxiv-cs-lg

INFORM-CT: INtegrating LLMs and VLMs FOR Incidental Findings Management in Abdominal CT

arXiv:2512.14732v2 Announce Type: replace-cross Abstract: Incidental findings in CT scans, though often benign, can have significant clinical implications and should be reported following established

Tutorials

Instantiating Bayesian CVaR lower bounds in Interactive Decision Making Problems

arXiv:2604.12519v1 Announce Type: new Abstract: Recent work established a generalized-Fano framework for lower bounding prior-predictive (Bayesian) CVaR in interactive statistical decision making. In

tutorialsarxiv-cs-lg

INTARG: Informed Real-Time Adversarial Attack Generation for Time-Series Regression

arXiv:2604.11928v1 Announce Type: new Abstract: Time-series forecasting aims to predict future values by modeling temporal dependencies in historical observations. It is a critical component of many r

applicationsarxiv-cs-lg

Hardware

ISSCC 2026: NVIDIA & Broadcom CPO, HBM4 & LPDDR6, TSMC Active LSI, Logic-Based SRAM, UCIe-S and More

ISSCC 2026 previews cutting-edge semiconductor research and industry presentations covering co-packaged optics (CPO) developments from NVIDIA and Broadcom, next-generation memory standards including H

hardwaresemianalysis

KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning

arXiv:2604.12487v1 Announce Type: cross Abstract: Large Language Models (LLMs) exhibit strong abilities in natural language understanding and generation, yet they struggle with knowledge-intensive rea

Latent-Condensed Transformer for Efficient Long Context Modeling

arXiv:2604.12452v1 Announce Type: new Abstract: Large language models (LLMs) face significant challenges in processing long contexts due to the linear growth of the key-value (KV) cache and quadratic

researcharxiv-cs-cl

Latent Planning Emerges with Scale

arXiv:2604.12493v1 Announce Type: cross Abstract: LLMs can perform seemingly planning-intensive tasks, like writing coherent stories or functioning code, without explicitly verbalizing a plan; however

Learned Incremental Nonlinear Dynamic Inversion for Quadrotors with and without Slung Payloads

arXiv:2503.09441v2 Announce Type: replace Abstract: The increasing complexity of multirotor applications demands flight controllers that can accurately account for all forces acting on the vehicle. Co

researcharxiv-cs-ro

Leveraging Weighted Syntactic and Semantic Context Assessment Summary (wSSAS) Towards Text Categorization Using LLMs

arXiv:2604.12049v1 Announce Type: cross Abstract: The use of Large Language Models (LLMs) for reliable, enterprise-grade analytics such as text categorization is often hindered by the stochastic natur

Agents

LIFE -- an energy efficient advanced continual learning agentic AI framework for frontier systems

arXiv:2604.12874v1 Announce Type: new Abstract: The rapid advancement of AI has changed the character of HPC usage such as dimensioning, provisioning, and execution. Not only has energy demand been am

agentsarxiv-cs-ai

Tutorials

Listening Deepfake Detection: A New Perspective Beyond Speaking-Centric Forgery Analysis

arXiv:2604.12650v1 Announce Type: new Abstract: Existing deepfake detection research has primarily focused on scenarios where the manipulated subject is actively speaking, i.e., generating fabricated

tutorialsarxiv-cs-cv

LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark of Large Language Models for Automated System Diagnostics

arXiv:2604.12218v1 Announce Type: new Abstract: System log anomaly detection is critical for maintaining the reliability of large-scale software systems, yet traditional methods struggle with the hete

LLM-Guided Prompt Evolution for Password Guessing

arXiv:2604.12601v1 Announce Type: cross Abstract: Passwords still remain a dominant authentication method, yet their security is routinely subverted by predictable user choices and large-scale credent

Local Ai

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models

arXiv:2601.14004v4 Announce Type: replace Abstract: Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However,

local-aiarxiv-cs-cl

LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Software

arXiv:2604.12994v1 Announce Type: cross Abstract: Logical vulnerabilities in software stem from flaws in program logic rather than memory safety, which can lead to critical security failures. Although

Meet Dynamic Individual Preferences: Resolving Conflicting Human Value with Paired Fine-Tuning

arXiv:2604.12479v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have significantly improved the alignment of models with general human preferences. However, a major cha

safetyarxiv-cs-cl

Mining Large Language Models for Low-Resource Language Data: Comparing Elicitation Strategies for Hausa and Fongbe

arXiv:2604.12477v1 Announce Type: cross Abstract: Large language models (LLMs) are trained on data contributed by low-resource language communities, yet the linguistic knowledge encoded in these model

Mixed-Integer vs. Continuous Model Predictive Control for Binary Thrusters: A Comparative Study

arXiv:2603.19796v3 Announce Type: replace-cross Abstract: Binary on/off thrusters are commonly used for spacecraft attitude and position control during proximity operations. However, their discrete na

researcharxiv-cs-ro

Monte Carlo Stochastic Depth for Uncertainty Estimation in Deep Learning

arXiv:2604.12719v1 Announce Type: new Abstract: The deployment of deep neural networks in safety-critical systems necessitates reliable and efficient uncertainty quantification (UQ). A practical and w

@NousResearch Creative Director is working overtime 😁

Nous Research's Creative Director appears to be putting in significant effort on a project or initiative, as highlighted in a lighthearted post from the organization's X (formerly Twitter) account. Th

researchnous-research--x

Agents

OctoTools: An Agentic Framework with Extensible Tools for Complex Reasoning

arXiv:2502.11271v2 Announce Type: replace-cross Abstract: Solving complex reasoning tasks may involve visual understanding, domain knowledge retrieval, numerical calculation, and multi-step reasoning.

agentsarxiv-cs-cl

One Model for All: Unified Try-On and Try-Off in Any Pose via LLM-Inspired Bidirectional Tweedie Diffusion

arXiv:2508.04559v3 Announce Type: replace Abstract: Recent diffusion-based approaches have made significant advances in image-based virtual try-on, enabling more realistic and end-to-end garment synth

applicationsarxiv-cs-cv

OSC: Hardware Efficient W4A4 Quantization via Outlier Separation in Channel Dimension

arXiv:2604.12782v1 Announce Type: cross Abstract: While 4-bit quantization is essential for high-throughput deployment of Large Language Models, activation outliers often lead to significant accuracy

Parallax: Why AI Agents That Think Must Never Act

arXiv:2604.12986v1 Announce Type: cross Abstract: Autonomous AI agents are rapidly transitioning from experimental tools to operational infrastructure, with projections that 80% of enterprise applicat

Physics-Grounded Monocular Vehicle Distance Estimation Using Standardized License Plate Typography

arXiv:2604.12239v1 Announce Type: new Abstract: Accurate inter-vehicle distance estimation is a cornerstone of Advanced Driver Assistance Systems (ADAS) and autonomous driving. While LiDAR and radar p

safetyarxiv-cs-cv

Polynomial Expansion Rank Adaptation: Enhancing Low-Rank Fine-Tuning with High-Order Interactions

arXiv:2604.11841v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) is a widely used strategy for efficient fine-tuning of large language models (LLMs), but its strictly linear structure fund

Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints

arXiv:2604.12384v1 Announce Type: new Abstract: Safety alignment in Large Language Models (LLMs) remains highly fragile during fine-tuning, where even benign adaptation can degrade pre-trained refusal

Privacy-Preserving Structureless Visual Localization via Image Obfuscation

arXiv:2604.12068v1 Announce Type: new Abstract: Visual localization is the task of estimating the camera pose of an image relative to a scene representation. In practice, visual localization systems a

researcharxiv-cs-cv

Prompt Evolution for Generative AI: A Classifier-Guided Approach

arXiv:2305.16347v2 Announce Type: replace-cross Abstract: Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with genera

Public Profile Matters: A Scalable Integrated Approach to Recommend Citations in the Wild

arXiv:2603.17361v2 Announce Type: replace-cross Abstract: Proper citation of relevant literature is essential for contextualising and validating scientific contributions. While current citation recomm

RegD: Hierarchical Embeddings via Dissimilarity between Arbitrary Euclidean Regions

arXiv:2501.17518v3 Announce Type: replace-cross Abstract: Hierarchical data is common in many domains like life sciences and e-commerce, and its embeddings often play a critical role. While hyperbolic

applicationsarxiv-cs-ai

Reliability-Guided Depth Fusion for Glare-Resilient Navigation Costmaps

arXiv:2604.12753v1 Announce Type: new Abstract: Specular glare on reflective floors and glass surfaces frequently corrupts RGB-D depth measurements, producing holes and spikes that accumulate as persi

safetyarxiv-cs-ro

ResBM: Residual Bottleneck Models for Low-Bandwidth Pipeline Parallelism

arXiv:2604.11947v1 Announce Type: cross Abstract: Unlocking large-scale low-bandwidth decentralized training has the potential to utilize otherwise untapped compute resources. In centralized settings,