Search: “papers”

RPRA: Predicting an LLM-Judge for Efficient but Performant Inference

arXiv:2604.12634v1 Announce Type: new Abstract: Large language models (LLMs) face a fundamental trade-off between computational efficiency (e.g., number of parameters) and output quality, especially w

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

RSGMamba: Reliability-Aware Self-Gated State Space Model for Multimodal Semantic Segmentation

DGX agent

arXiv:2604.12319v1 Announce Type: new Abstract: Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multi

researcharxiv-cs-cv

15 Apr 2026

Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework

arXiv:2509.18127v3 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) enable interpretability research by decomposing entangled model activations into monosemantic features. However, un

Scalable and General Whole-Body Control for Cross-Humanoid Locomotion

arXiv:2602.05791v2 Announce Type: replace Abstract: Learning-based whole-body controllers have become a key driver for humanoid robots, yet most existing approaches require robot-specific training. In

safetyarxiv-cs-ro

SinkSAM-Net: Knowledge-Driven Self-Supervised Sinkhole Segmentation Using Topographic Priors and Segment Anything Model

arXiv:2410.01473v2 Announce Type: replace Abstract: Soil sinkholes significantly influence soil degradation, infrastructure vulnerability, and landscape evolution. However, their irregular shapes, com

Applications

SmellNet: A Large-scale Dataset for Real-world Smell Recognition

arXiv:2506.00239v5 Announce Type: replace Abstract: The ability of AI to sense and identify various substances based on their smell alone can have profound impacts on allergen detection (e.g. smelling

applicationsarxiv-cs-ai

Socrates Loss: Unifying Confidence Calibration and Classification by Leveraging the Unknown

arXiv:2604.12245v1 Announce Type: cross Abstract: Deep neural networks, despite their high accuracy, often exhibit poor confidence calibration, limiting their reliability in high-stakes applications.

Subspace-Guided Feature Reconstruction for Unsupervised Anomaly Localization

arXiv:2309.13904v3 Announce Type: replace Abstract: Unsupervised anomaly localization aims to identify anomalous regions that deviate from normal sample patterns. Most recent methods perform feature m

Synthetic POMDPs to Challenge Memory-Augmented RL: Memory Demand Structure Modeling

arXiv:2508.04282v3 Announce Type: replace Abstract: Recent benchmarks for memory-augmented reinforcement learning (RL) have introduced partially observable Markov decision process (POMDP) environments

SynthPix: A lightspeed PIV image generator

arXiv:2512.09664v2 Announce Type: replace-cross Abstract: We describe SynthPix, a synthetic image generator for Particle Image Velocimetry (PIV) with a focus on performance and parallelism on accelera

TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning

model-releasesarxiv-cs-lg

arXiv:2604.12891v1 Announce Type: new Abstract: Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on

Teaching LLMs Human-Like Editing of Inappropriate Argumentation via Reinforcement Learning

arXiv:2604.12770v1 Announce Type: new Abstract: Editing human-written text has become a standard use case of large language models (LLMs), for example, to make one's arguments more appropriate for a d

safetyarxiv-cs-cl

TEMPLATEFUZZ: Fine-Grained Chat Template Fuzzing for Jailbreaking and Red Teaming LLMs

arXiv:2604.12232v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed across diverse domains, yet their vulnerability to jailbreak attacks, where adversarial inputs

Ternary Logic Encodings of Temporal Behavior Trees with Application to Control Synthesis

arXiv:2604.12092v1 Announce Type: new Abstract: Behavior Trees (BTs) provide designers an intuitive graphical interface to construct long-horizon plans for autonomous systems. To ensure their correctn

safetyarxiv-cs-ro

The Linear Centroids Hypothesis: How Deep Network Features Represent Data

arXiv:2604.11962v1 Announce Type: new Abstract: Identifying and understanding the features that a deep network (DN) extracts from its inputs to produce its outputs is a focal point of interpretability

researcharxiv-cs-lg

The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap

arXiv:2604.11828v1 Announce Type: new Abstract: Science is widely regarded as humanity's most reliable method for uncovering truths about the natural world. Yet the trajectory of scientific discovery

Thought-Retriever: Don't Just Retrieve Raw Data, Retrieve Thoughts for Memory-Augmented Agentic Systems

model-releasesarxiv-cs-cl

arXiv:2604.12231v1 Announce Type: new Abstract: Large language models (LLMs) have transformed AI research thanks to their powerful internal capabilities and knowledge. However, existing LLMs still fai

Local Ai

Time-reversed Flow Matching with Worst Transport in High-dimensional Latent Space for Image Anomaly Detection

arXiv:2508.05461v3 Announce Type: replace Abstract: Likelihood-based deep generative models have been widely investigated for Image Anomaly Detection (IAD), particularly Normalizing Flows, yet their s

local-aiarxiv-cs-cv

Topology-Aware Reasoning over Incomplete Knowledge Graph with Graph-Based Soft Prompting

arXiv:2604.12503v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable capabilities across various tasks but remain prone to hallucinations in knowledge-intensive scenari

Towards EnergyGPT: A Large Language Model Specialized for the Energy Sector

model-releasesarxiv-cs-cl

arXiv:2509.07177v3 Announce Type: replace Abstract: Large language models have demonstrated impressive capabilities across various domains. However, their general-purpose nature often limits their eff

Towards Platonic Representation for Table Reasoning: A Foundation for Permutation-Invariant Retrieval

arXiv:2604.12133v1 Announce Type: new Abstract: Historical approaches to Table Representation Learning (TRL) have largely adopted the sequential paradigms of Natural Language Processing (NLP). We argu

Transformer Based Machine Fault Detection From Audio Input

model-releasesarxiv-cs-lg

arXiv:2604.12733v1 Announce Type: cross Abstract: In recent years, Sound AI is being increasingly used to predict machine failures. By attaching a microphone to the machine of interest, one can get re

Turbo-DDCM: Fast and Flexible Zero-Shot Diffusion-Based Image Compression

arXiv:2511.06424v2 Announce Type: replace-cross Abstract: While zero-shot diffusion-based compression methods have seen significant progress in recent years, they remain notoriously slow and computati

Understanding and Improving Continuous Adversarial Training for LLMs via In-context Learning Theory

arXiv:2604.12817v1 Announce Type: new Abstract: Adversarial training (AT) is an effective defense for large language models (LLMs) against jailbreak attacks, but performing AT on LLMs is costly. To im

safetyarxiv-cs-lg

V-Nutri: Dish-Level Nutrition Estimation from Egocentric Cooking Videos

arXiv:2604.11913v1 Announce Type: new Abstract: Nutrition estimation of meals from visual data is an important problem for dietary monitoring and computational health, but existing approaches largely

Variation in Verification: Understanding Verification Dynamics in Large Language Models

arXiv:2509.17995v2 Announce Type: replace-cross Abstract: Recent advances have shown that scaling test-time computation enables large language models (LLMs) to solve increasingly complex problems acro

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling

arXiv:2505.17384v2 Announce Type: replace-cross Abstract: Discrete diffusion models have recently shown great promise for modeling complex discrete data, with masked diffusion models (MDMs) offering a

researcharxiv-cs-cv

Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices

arXiv:2512.06443v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed on edge devices. To meet strict resource constraints, real-world deployment has pushed

Hardware

VFA: Relieving Vector Operations in Flash Attention with Global Maximum Pre-computation

arXiv:2604.12798v1 Announce Type: cross Abstract: FlashAttention-style online softmax enables exact attention computation with linear memory by streaming score tiles through on-chip memory and maintai

hardwarearxiv-cs-ai

Vision Transformers Need More Than Registers

arXiv:2602.22394v2 Announce Type: replace Abstract: Vision Transformers (ViTs), when pre-trained on large-scale data, provide general-purpose representations for diverse downstream tasks. However, art

researcharxiv-cs-cv

VULCAN: Vision-Language-Model Enhanced Multi-Agent Cooperative Navigation for Indoor Fire-Disaster Response

model-releasesarxiv-cs-ro

arXiv:2604.12831v1 Announce Type: new Abstract: Indoor fire disasters pose severe challenges to autonomous search and rescue due to dense smoke, high temperatures, and dynamically evolving indoor envi

Agents

When to Forget: A Memory Governance Primitive

arXiv:2604.12007v1 Announce Type: new Abstract: Agent memory systems accumulate experience but currently lack a principled operational metric for memory quality governance -- deciding which memories t

agentsarxiv-cs-ai

Why Did Apple Fall: Evaluating Curiosity in Large Language Models

arXiv:2510.20635v2 Announce Type: replace-cross Abstract: Curiosity serves as a pivotal conduit for human beings to discover and learn new knowledge. Recent advancements of large language models (LLMs

WikiSeeker: Rethinking the Role of Vision-Language Models in Knowledge-Based Visual Question Answering

model-releasesarxiv-cs-cl

arXiv:2604.05818v2 Announce Type: replace-cross Abstract: Multi-modal Retrieval-Augmented Generation (RAG) has emerged as a highly effective paradigm for Knowledge-Based Visual Question Answering (KB-

A Benchmark for Gap and Overlap Analysis as a Test of KG Task Readiness

arXiv:2604.10853v1 Announce Type: new Abstract: Task-oriented evaluation of knowledge graph (KG) quality increasingly asks whether an ontology-based representation can answer the competency questions

A Compact and Efficient 1.251 Million Parameter Machine Learning CNN Model PD36-C for Plant Disease Detection: A Case Study

arXiv:2604.11332v1 Announce Type: cross Abstract: Deep learning has markedly advanced image based plant disease diagnosis as improved hardware and dataset quality have enabled increasingly accurate ne

A Comparative Theoretical Analysis of Entropy Control Methods in Reinforcement Learning

arXiv:2604.09676v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a key approach for enhancing reasoning in large language models (LLMs), yet scalable training is often hindered

A Dual-Positive Monotone Parameterization for Multi-Segment Bids and a Validity Assessment Framework for Reinforcement Learning Agent-based Simulation of Electricity Markets

arXiv:2604.10252v1 Announce Type: new Abstract: Reinforcement learning agent-based simulation (RL-ABS) has become an important tool for electricity market mechanism analysis and evaluation. In the mod

A Mechanistic Analysis of Looped Reasoning Language Models

arXiv:2604.11791v1 Announce Type: cross Abstract: Reasoning has become a central capability in large language models. Recent research has shown that reasoning performance can be improved by looping an

A Multi-head Attention Fusion Network for Industrial Prognostics under Discrete Operational Conditions

arXiv:2604.10248v1 Announce Type: new Abstract: Complex systems such as aircraft engines, turbines, and industrial machinery often operate under dynamically changing conditions. These varying operatin

researcharxiv-cs-lg

A Proposed Biomedical Data Policy Framework to Reduce Fragmentation, Improve Quality, and Incentivize Sharing in Indian Healthcare in the era of Artificial Intelligence and Digital Health

arXiv:2604.11125v1 Announce Type: new Abstract: India generates vast biomedical data through postgraduate research, government hospital services and audits, government schemes, private hospitals and t

A Survey of Inductive Reasoning for Large Language Models

arXiv:2510.10182v2 Announce Type: replace-cross Abstract: Reasoning is an important task for large language models (LLMs). Among all the reasoning paradigms, inductive reasoning is one of the fundamen

A Survey on 3D Gaussian Splatting Applications: Segmentation, Editing, and Generation

arXiv:2508.09977v4 Announce Type: replace Abstract: In the context of novel view synthesis, 3D Gaussian Splatting (3DGS) has recently emerged as an efficient and competitive counterpart to Neural Radi

researcharxiv-cs-cv

A Temporally Augmented Graph Attention Network for Affordance Classification

arXiv:2604.10149v1 Announce Type: cross Abstract: Graph attention networks (GATs) provide one of the best frameworks for learning node representations in relational data; but, existing variants such a

AbLWR:A Context-Aware Listwise Ranking Framework for Antibody-Antigen Binding Affinity Prediction via Positive-Unlabeled Learning

arXiv:2604.11272v1 Announce Type: cross Abstract: Accurate prediction of antibody-antigen binding affinity is fundamental to therapeutic design, yet remains constrained by severe label sparsity and th

AC-MIL: Weakly Supervised Atrial LGE-MRI Quality Assessment via Adversarial Concept Disentanglement

arXiv:2604.10303v1 Announce Type: new Abstract: High-quality Late Gadolinium Enhancement (LGE) MRI can be helpful for atrial fibrillation management, yet scan quality is frequently compromised by pati

Agents

AccidentSim: Generating Vehicle Collision Videos with Physically Realistic Collision Trajectories from Real-World Accident Reports

arXiv:2503.20654v4 Announce Type: replace-cross Abstract: Collecting real-world vehicle accident videos for autonomous driving research is challenging due to their rarity and complexity. While existin

agentsarxiv-cs-ai

Agents

ADAM: A Systematic Data Extraction Attack on Agent Memory via Adaptive Querying

arXiv:2604.09747v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have achieved rapid adoption and demonstrated remarkable capabilities across a wide range of applications. To improv

agentsarxiv-cs-ai