Search: “context”

NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium

arXiv:2510.25977v4 Announce Type: replace Abstract: Emerging AI accelerators have started to gain attention and offer new opportunities for efficient inference of large language models (LLMs). Trainiu

researcharxiv-cs-cl

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Optimal Lower Bounds for Online Multicalibration

DGX agent

arXiv:2601.05245v2 Announce Type: replace Abstract: We prove tight lower bounds for online multicalibration, establishing an information-theoretic separation from marginal calibration. In the general

researcharxiv-cs-lg

27 Apr 2026

Source-Modality Monitoring in Vision-Language Models

arXiv:2604.22038v1 Announce Type: new Abstract: We define and investigate source-modality monitoring -- the ability of multimodal models to track and communicate the input source from which pieces of

agentsarxiv-cs-cl

Hardware

Toward Robust and Efficient ML-Based GPU Caching for Modern Inference

arXiv:2509.20979v2 Announce Type: replace Abstract: In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as extsc{LRU} can perform far worse than the offli

hardwarearxiv-cs-lg

When Quotes Crumble: Detecting Transient Mechanical Liquidity Erosion in Limit Order Books

arXiv:2604.21993v1 Announce Type: new Abstract: We study the detection of transient liquidity erosion ('crumbling quotes') in electronic limit order books, where observable quote deterioration may ref

agentsarxiv-cs-lg

A-IC3: Learning-Guided Adaptive Inductive Generalization for Hardware Model Checking

model-releasesarxiv-cs-lg

arXiv:2604.21688v1 Announce Type: cross Abstract: The IC3 algorithm represents the state-of-the-art (SOTA) hardware model checking technique, owing to its robust performance and scalability. A signifi

A Scale-Adaptive Framework for Joint Spatiotemporal Super-Resolution with Diffusion Models

arXiv:2604.21903v1 Announce Type: cross Abstract: Deep-learning video super-resolution has progressed rapidly, but climate applications typically super-resolve (increase resolution) either space or ti

Adaptive Defense Orchestration for RAG: A Sentinel-Strategist Architecture against Multi-Vector Attacks

arXiv:2604.20932v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private, do

Tutorials

Adaptive Instruction Composition for Automated LLM Red-Teaming

arXiv:2604.21159v1 Announce Type: cross Abstract: Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with identifyin

tutorialsarxiv-cs-ai

An Overlay Multicast Routing Method Based on Network Situational Awareness and Hierarchical Multi-Agent Reinforcement Learning

arXiv:2602.13211v2 Announce Type: replace-cross Abstract: Compared with IP multicast, Overlay Multicast (OM) offers better compatibility and flexible deployment in heterogeneous, cross-domain networks

agentsarxiv-cs-ai

Hardware

Association Is Not Similarity: Learning Corpus-Specific Associations for Multi-Hop Retrieval

arXiv:2604.20850v1 Announce Type: cross Abstract: Dense retrieval systems rank passages by embedding similarity to a query, but multi-hop questions require passages that are associatively related thro

hardwarearxiv-cs-ai

BackPlay: Head-Only Look-Back Self-Correction for Diffusion Language Models

arXiv:2601.06428v3 Announce Type: replace Abstract: Diffusion Language Models (DLMs) decode multiple tokens in parallel, but aggressive multi-token decoding amplifies cross-token dependency errors and

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos

arXiv:2504.07940v3 Announce Type: replace Abstract: 360{eg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the 'tunnel vision' of standard cameras, their

researcharxiv-cs-cv

CARE: Counselor-Aligned Response Engine for Online Mental-Health Support

arXiv:2604.21352v1 Announce Type: new Abstract: Mental health challenges are increasing worldwide, straining emotional support services and leading to counselor overload. This can result in delayed re

safetyarxiv-cs-cl

Cross-Session Threats in AI Agents: Benchmark, Evaluation, and Algorithms

arXiv:2604.21131v1 Announce Type: cross Abstract: AI-agent guardrails are memoryless: each message is judged in isolation, so an adversary who spreads a single attack across dozens of sessions slips p

Data-Driven Open-Loop Simulation for Digital-Twin Operator Decision Support in Wastewater Treatment

arXiv:2604.20935v1 Announce Type: cross Abstract: Wastewater treatment plants (WWTPs) need digital-twin-style decision support tools that can simulate plant response under prescribed control plans, to

Directional Confusions Reveal Divergent Inductive Biases Through Rate-Distortion Geometry in Human and Machine Vision

arXiv:2604.21909v1 Announce Type: new Abstract: Humans and modern vision models can reach similar classification accuracy while making systematically different kinds of mistakes - differing not in how

safetyarxiv-cs-cv

KinetiDiff: Docking-Guided Diffusion for De Novo ACVR1 Inhibitor Design in Fibrodysplasia Ossificans Progressiva

arXiv:2604.20886v1 Announce Type: cross Abstract: We present KinetiDiff, a structure-based framework for de novo kinase inhibitor design that integrates a Geometry-Complete Diffusion Model with real-t

KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems

arXiv:2508.10177v3 Announce Type: replace Abstract: Recent Large Language Model (LLM)-based AutoML systems demonstrate impressive capabilities but face significant limitations such as constrained expl

Local Neighborhood Instability in Parametric Projections: Quantitative and Visual Analysis

arXiv:2604.21617v1 Announce Type: new Abstract: Parametric projections let analysts embed new points in real time, but input variations from measurement noise or data drift can produce unpredictable s

safetyarxiv-cs-cv

Mapping the Political Discourse in the Brazilian Chamber of Deputies: A Multi-Faceted Computational Approach

arXiv:2604.21897v1 Announce Type: new Abstract: Analyses of legislative behavior often rely on voting records, overlooking the rich semantic and rhetorical content of political speech. In this paper,

applicationsarxiv-cs-cl

Multimodal Protein Language Models for Enzyme Kinetic Parameters: From Substrate Recognition to Conformational Adaptation

arXiv:2603.12845v2 Announce Type: replace Abstract: Predicting enzyme kinetic parameters quantifies how efficiently an enzyme catalyzes a specific substrate under defined biochemical conditions. Canon

safetyarxiv-cs-cv

Not-a-Bandit: Provably No-Regret Drafter Selection in Speculative Decoding for LLMs

arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection

Planning Beyond Text: Graph-based Reasoning for Complex Narrative Generation

arXiv:2604.21253v1 Announce Type: cross Abstract: While LLMs demonstrate remarkable fluency in narrative generation, existing methods struggle to maintain global narrative coherence, contextual logica

Satisfying Rationality Postulates of Structured Argumentation Through Deductive Support -- Technical Report

arXiv:2604.21515v1 Announce Type: new Abstract: ASPIC-style structured argumentation frameworks provide a formal basis for reasoning in artificial intelligence by combining internal argument structure

Sink-Token-Aware Pruning for Fine-Grained Video Understanding in Efficient Video LLMs

arXiv:2604.20937v1 Announce Type: new Abstract: Video Large Language Models (Video LLMs) incur high inference latency due to a large number of visual tokens provided to LLMs. To address this, training

Strategic Polysemy in AI Discourse: A Philosophical Analysis of Language, Hype, and Power

arXiv:2604.21043v1 Announce Type: cross Abstract: This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metap

safetyarxiv-cs-ai

StructMem: Structured Memory for Long-Horizon Behavior in LLMs

arXiv:2604.21748v1 Announce Type: cross Abstract: Long-term conversational agents need memory systems that capture relationships between events, not merely isolated facts, to support temporal reasonin

Task-specific Subnetwork Discovery in Reinforcement Learning for Autonomous Underwater Navigation

arXiv:2604.21640v1 Announce Type: cross Abstract: Autonomous underwater vehicles are required to perform multiple tasks adaptively and in an explainable manner under dynamic, uncertain conditions and

safetyarxiv-cs-ai

Transfer Learning for Loan Recovery Prediction under Distribution Shifts with Heterogeneous Feature Spaces

arXiv:2604.02832v2 Announce Type: replace-cross Abstract: Accurate forecasting of recovery rates (RR) is central to credit risk management and regulatory capital determination. In many loan portfolios

applicationsarxiv-cs-lg

Transferable SCF-Acceleration through Solver-Aligned Initialization Learning

arXiv:2604.21657v1 Announce Type: new Abstract: Machine learning methods that predict initial guesses from molecular geometry can reduce this cost, but matrix-prediction models fail when extrapolating

VVS: Accelerating Speculative Decoding for Visual Autoregressive Generation via Partial Verification Skipping

arXiv:2511.13587v2 Announce Type: replace-cross Abstract: Visual autoregressive (AR) generation models have demonstrated strong potential for image generation, yet their next-token-prediction paradigm

AI to Learn 2.0: A Deliverable-Oriented Governance Framework and Maturity Rubric for Opaque AI in Learning-Intensive Domains

arXiv:2604.19751v1 Announce Type: new Abstract: Generative AI is entering research, education, and professional work faster than current governance frameworks can specify how AI-assisted outputs shoul

An explicit operator explains end-to-end computation in the modern neural networks used for sequence and language modeling

arXiv:2604.20595v1 Announce Type: cross Abstract: We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data,

applicationsarxiv-cs-lg

Behavioral Transfer in AI Agents: Evidence and Privacy Implications

arXiv:2604.19925v1 Announce Type: cross Abstract: AI agents powered by large language models are increasingly acting on behalf of humans in social and economic environments. Prior research has focused

agentsarxiv-cs-ai

Control Consistency Losses for Diffusion Bridges

arXiv:2512.05070v2 Announce Type: replace-cross Abstract: Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem i

Diagnosing CFG Interpretation in LLMs

arXiv:2604.20811v1 Announce Type: new Abstract: As LLMs are increasingly integrated into agentic systems, they must adhere to dynamically defined, machine-interpretable interfaces. We evaluate LLMs as

safetyarxiv-cs-ai

Local Ai

FA-Seg: A Fast and Accurate Diffusion-Based Method for Open-Vocabulary Segmentation

arXiv:2506.23323v5 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Al

local-aiarxiv-cs-cv

FlashNorm: Fast Normalization for Transformers

model-releasesarxiv-cs-lg

arXiv:2407.09577v4 Announce Type: replace Abstract: Normalization layers are ubiquitous in large language models (LLMs) yet represent a compute bottleneck: on hardware with distinct vector and matrix

HumanScore: Benchmarking Human Motions in Generated Videos

arXiv:2604.20157v1 Announce Type: new Abstract: Recent advances in model architectures, compute, and data scale have driven rapid progress in video generation, producing increasingly realistic content

researcharxiv-cs-cv

Improving End-to-End Training of Retrieval-Augmented Generation Models via Joint Stochastic Approximation

arXiv:2508.18168v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has become a widely recognized paradigm to combine parametric memory with non-parametric memories. An RAG model

researcharxiv-cs-cl

Interpretability from the Ground Up: Stakeholder-Centric Design of Automated Scoring in Educational Assessments

arXiv:2511.17069v3 Announce Type: replace Abstract: AI-driven automated scoring systems offer scalable and efficient means of evaluating complex student-generated responses. Yet, despite increasing de

applicationsarxiv-cs-cl

MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy

arXiv:2511.11931v2 Announce Type: replace Abstract: This paper proposes MATT-Diff: Multimodal Active Target Tracking by Diffusion Policy, a control policy for active multi-target tracking using a mobi

safetyarxiv-cs-ro

NanoCockpit: Performance-optimized Application Framework for AI-based Autonomous Nanorobotics

arXiv:2601.07476v2 Announce Type: replace Abstract: Autonomous nano-drones, powered by vision-based tiny machine learning (TinyML) models, are a novel technology gaining momentum thanks to their broad

agentsarxiv-cs-ro

Near-Future Policy Optimization

arXiv:2604.20733v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a core post-training recipe. Introducing suitable off-policy trajectories into on-polic

safetyarxiv-cs-lg

On-Meter Graph Machine Learning: A Case Study of PV Power Forecasting for Grid Edge Intelligence

arXiv:2604.19800v1 Announce Type: cross Abstract: This paper presents a detailed study of how graph neural networks can be used on edge intelligent meters in a microgrid to forecast photovoltaic power

applicationsarxiv-cs-ai

Local Ai

Online Structure Learning and Planning for Autonomous Robot Navigation using Active Inference

arXiv:2510.09574v2 Announce Type: replace Abstract: Autonomous navigation in unfamiliar environments requires robots to simultaneously explore, localise, and plan under uncertainty, without relying on

local-aiarxiv-cs-ro

Prism: An Evolutionary Memory Substrate for Multi-Agent Open-Ended Discovery

arXiv:2604.19795v1 Announce Type: new Abstract: We introduce prism{} (extbf{P}robabilistic extbf{R}etrieval with extbf{I}nformation-extbf{S}tratified extbf{M}emory), an evolutionary memory substrate f