Search: “context”

UrduMMLU: A Massive Multitask Benchmark for Urdu Language Understanding

arXiv:2606.07167v1 Announce Type: cross Abstract: Meaningful multilingual evaluation must test models in the target language and educational context. Urdu, spoken by more than 230 million people, lack

8 Jun 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

QCFuse: Query-Aware Cache Fusion via Compressed View for Efficient RAG Serving

DGX agent

arXiv:2606.05875v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language model (LLM) answer quality by grounding generation in external evidence, but processing ret

researcharxiv-cs-ai

6 Jun 2026

Towards Unified and Data-Efficient Prognostics and Health Management with Tabular Foundation Models

arXiv:2606.05481v1 Announce Type: cross Abstract: Data-driven Prognostics and Health Management (PHM) uses time-varying condition-monitoring data to diagnose system states and estimate remaining usefu

6 Jun 2026

When Good Enough Is Optimal: Multiplication-Only Matrix Inversion Approximation for Quantized Gated DeltaNet

arXiv:2606.06034v1 Announce Type: cross Abstract: Matrix inversion in chunk-wise parallel linear attention is a major bottleneck for long-context modeling, particularly on NPUs, where forward-substitu

6 Jun 2026

Code2LoRA: Hypernetwork-Generated Adapters for Code Language Models under Software Evolution

arXiv:2606.06492v1 Announce Type: cross Abstract: Code language models need repository-level context to resolve imports, APIs, and project conventions. Existing methods inject this knowledge as long i

EMBER: Efficient Memory via Budgeted Evidence Retention for Long-Horizon Agents

arXiv:2606.05894v1 Announce Type: new Abstract: Long-horizon agents can archive large histories, but future answers still incur retrieval, rereading, and context costs. When retained memory misses ans

safetyarxiv-cs-cl

Gender Artifacts from Art History to Text-to-Image Generation

arXiv:2606.05829v1 Announce Type: new Abstract: Artistic styles are rooted in specific socio-historical contexts that encode social hierarchies, including distinct constructions of gender. Yet in AI r

researcharxiv-cs-cv

Grounded but Misleading: Evaluating Semantic Alignment in AI-Generated Security Explanations

arXiv:2602.05056v2 Announce Type: replace-cross Abstract: Online scams increasingly leverage fluent and context-aware social engineering strategies, creating growing demand for AI systems that explain

safetyarxiv-cs-cl

Local Ai

LeanMarathon: Toward Reliable AI Co-Mathematicians through Long-Horizon Lean Autoformalization

arXiv:2606.05400v1 Announce Type: cross Abstract: Long-horizon autoformalization of research mathematics fails not only at hard lemmas, but at scale: statements drift, dependencies tangle, context dec

local-aiarxiv-cs-cl

Staying with the Uncertainty: Uncertainty-Scaffolding Strategies for Artificial Moral Advisors in LLM-to-LLM Simulated Conversations

arXiv:2606.05890v1 Announce Type: new Abstract: LLMs are increasingly deployed as Artificial Moral Advisors (AMA) in a variety of contexts: what kind of conversational patterns should they display? In

agentsarxiv-cs-cl

Beyond Prompt-Based Planning: MCP-Native Graph Planning-based Biomedical Agent System

arXiv:2606.04494v1 Announce Type: new Abstract: Biomedical agents promise to automate complex biological workflows, yet current systems face two fundamental bottlenecks: bioinformatics tools are highl

BioBlue: Systematic runaway-optimiser-like LLM failure modes on biologically and economically aligned AI safety benchmarks for LLMs with simplified observation format

arXiv:2509.02655v3 Announce Type: replace-cross Abstract: Many AI alignment discussions of 'runaway optimisation' focus on RL agents: unbounded utility maximisers that over-optimise a proxy objective

Caught in the Act(ivation): Toward Pre-Output and Multi-Turn Detection of Credential Exfiltration by LLM Agents

arXiv:2606.04141v1 Announce Type: cross Abstract: LLM agents often place sensitive credentials in the same context window as untrusted retrieved content, creating a direct path for indirect prompt inj

Description-Code Inconsistency in Real-world MCP Servers: Measurement, Detection, and Security Implications

arXiv:2606.04769v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as a critical standard empowering Large Language Models (LLMs) to utilize external tools. In this ecosyst

Dynamic Infilling Anchors for Format-Constrained Generation in Diffusion Large Language Models

arXiv:2606.04535v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer bidirectional attention and parallel generation, enabling them to exploit global context and naturally s

Exploring Cross-Scenario Generality of Agentic Memory Systems: Diagnostics and a Strong Baseline

arXiv:2606.04315v1 Announce Type: new Abstract: LLM agents accumulate histories that outgrow their context windows, motivating a growing literature on memory systems. Yet most existing designs are tun

Fast & Faithful Function Vectors

arXiv:2606.05079v1 Announce Type: new Abstract: Function vectors (FVs) are task representations elicited during in-context learning that can be used to steer Large Language Models (LLMs). However, des

From Prompt to Process: a Process Taxonomy and Comparative Assessment of Frameworks Supporting AI Software Development Agents

arXiv:2606.04967v1 Announce Type: cross Abstract: AI tools for programming are no longer just autocomplete or chat assistants: they organize themselves as development frameworks, with process, roles,

Global Sketch-Based Watermarking for Diffusion Language Models

arXiv:2606.04486v1 Announce Type: cross Abstract: Watermarking methods for language models have been studied extensively in the autoregressive setting, where tokens are generated sequentially. These w

safetyarxiv-cs-cl

Light or Full Verb? A Minimal-Pair Dataset for Probing Phraseological Competence in Language Models

arXiv:2606.05087v1 Announce Type: new Abstract: Frequent English verbs such as 'have' and 'make' can function either as collocates in light-verb constructions or as full lexical predicates, as in 'mak

MaskForge: Structure-Aware Adaptive Attacks for Jailbreaking Diffusion Large Language Models

arXiv:2606.04027v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising partially masked sequences under bidirectional context, exposing a safe

MesaNet: Sequence Modeling by Locally Optimal Test-Time Training

arXiv:2506.05233v2 Announce Type: replace-cross Abstract: Sequence modeling is currently dominated by causal transformer architectures that use softmax self-attention. Although widely adopted, transfo

RAMPART: Registry-based Agentic Memory with Priority-Aware Runtime Transformation

arXiv:2606.04628v1 Announce Type: new Abstract: RAMPART is a compile-time memory model and pure in-RAM block registry for LLM-based agents. Context assembly is a programmable runtime operation where c

SaliMory: Orchestrating Cognitive Memory for Conversational Agents

arXiv:2606.04120v1 Announce Type: cross Abstract: Conversational agents that serve as lifelong companions must maintain persistent memory across all interactions. However, simply expanding context win

Self-Distilled Policy Gradient

arXiv:2606.04036v1 Announce Type: new Abstract: On-policy self-distillation, where a language model conditions on privileged context to supervise its own generations, is a promising source of dense su

safetyarxiv-cs-lg

Video2LoRA: Parametric Video Internalization for Vision-Language Models

arXiv:2606.04351v1 Announce Type: cross Abstract: Processing video in vision-language models is expensive: each frame occupies hundreds of tokens, and inference cost scales with every frame and every

Vision Transformer Finetuning Benefits from Non-Smooth Components

arXiv:2602.06883v3 Announce Type: replace-cross Abstract: The smoothness of the transformer architecture has been extensively studied in the context of generalization, training stability, and adversar

researcharxiv-cs-cv

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension

arXiv:2405.03386v2 Announce Type: replace Abstract: Training with noisy class labels impairs neural networks' generalization performance. In this context, mixup is a popular regularization technique t

researcharxiv-cs-lg

Capability Advertisement as a Market for Lemons: A Trust Layer for Heterogeneous Agent Networks

arXiv:2606.03034v1 Announce Type: cross Abstract: Large language model (LLM) agents have begun to delegate work to one another. Protocols such as the Model Context Protocol (MCP) and the Agent2Agent p

Tutorials

Data-Driven Forecasting of three-Component Seismograms Using Transformer Architectures

arXiv:2606.02912v1 Announce Type: cross Abstract: Forecasting seismic waveforms beyond observed data remains challenging due to the nonlinear, dispersive, and multi-scale nature of seismic wave propag

tutorialsarxiv-cs-lg

Neural Attention Search Linear: Towards Adaptive Token-Level Hybrid Attention Models

arXiv:2602.03681v2 Announce Type: replace Abstract: The quadratic computational complexity of softmax transformers has become a bottleneck in long-context scenarios. In contrast, linear attention mode

On dynamic multi-agent pathfinding methods: review, simulations and modifications

arXiv:2606.03735v1 Announce Type: cross Abstract: This paper presents a systematic study of pathfinding algorithms in the context of Dynamic Multi-Agent Pathfinding (D-MAPF), a setting that combines d

agentsarxiv-cs-ro

RGMem: Renormalization Group-inspired Memory Evolution for Language Agents

arXiv:2510.16392v3 Announce Type: replace Abstract: Personalized and continuous interactions are critical for LLM-based conversational agents, yet finite context windows and static parametric memory h

SEA-NLI: Natural Language Inference as a Lens into Southeast Asian Cultural Understanding

arXiv:2606.03284v1 Announce Type: new Abstract: Frontier LLMs perform well in Western contexts, but remain poorly tested on underrepresented cultures such as those in Southeast Asia (SEA). Existing NL

See Less, Specify More: Visual Evidence Budgets for Generalizable VLAs

arXiv:2606.02735v1 Announce Type: cross Abstract: Generalization remains a central bottleneck for vision-language-action (VLA) models: under distractors, appearance shifts, and semantically similar ta

A Theoretical Framework for Self-Play Theorem Proving Algorithms

arXiv:2606.01861v1 Announce Type: new Abstract: Self-play, a type of training algorithm that enables a model to self-improve, has recently shown promising empirical results in the context of formal th

researcharxiv-cs-lg

Absorbing Complexity: An Interaction-Native Knowledge Harness for Financial LLM Agents

arXiv:2606.01886v1 Announce Type: new Abstract: Financial AI agents often fail for a simple reason: they make users carry the complexity. A user must repeatedly restate goals, risk preferences, portfo

Adversarial Feeds Steer LLM Agent Decisions Against Their Defaults

arXiv:2606.00914v1 Announce Type: new Abstract: LLM agents increasingly act after consuming ranked external information streams such as social feeds, search results, retrieval contexts, and email queu

ART: Attention Run-time Termination for Efficient Large Language Model Decoding

arXiv:2606.00024v1 Announce Type: new Abstract: Long-context decoding in Large Language Models (LLMs) is severely constrained by the memory bandwidth required to fetch the extensive Key-Value (KV) cac

Connecting the Dots: Benchmarking Reflective Memory in Long-Horizon Dialogue

arXiv:2606.01223v1 Announce Type: cross Abstract: Despite substantial progress in long-context modeling, existing benchmarks remain confined to factual memory for explicit recall, failing to measure t

Diagnosing LLM Arbitration Behavior over Pre-evidence Epistemic States in RAG-based Fact-Checking

arXiv:2606.01120v1 Announce Type: new Abstract: In RAG-based fact-checking, LLMs are increasingly used as verifiers to check given claims against retrieved evidence. Their parametric knowledge can ind

Implicit Regularization for Multi-label Feature Selection

arXiv:2411.11436v2 Announce Type: replace-cross Abstract: In this paper, we address the problem of feature selection in the context of multi-label learning, by using a new estimator based on implicit

Learning to Remember, Learn, and Forget in Attention-Based Models

arXiv:2602.09075v3 Announce Type: replace-cross Abstract: In-Context Learning (ICL) in transformers acts as an online associative memory and is believed to underpin their high performance on complex s

Literary Emotions in Motion: A Soft Robotics Installation for Tactile Storytelling

arXiv:2606.00418v1 Announce Type: new Abstract: Soft robotics is increasingly explored in artistic contexts, where tactile interaction provides audiences with embodied engagement beyond visual or audi

researcharxiv-cs-ro

MCP-Persona: Benchmarking LLM Agents on Real-World Personal Applications via Environment Simulation

arXiv:2606.02470v1 Announce Type: new Abstract: The Model Context Protocol (MCP) has emerged as a transformative standard for connecting large language models (LLMs) with external data sources and too

Molecular Embedding-Based Algorithm Selection in Protein-Ligand Docking

model-releasesarxiv-cs-lg

arXiv:2512.02328v2 Announce Type: replace-cross Abstract: Selecting an effective docking algorithm is highly context-dependent, and no single method performs reliably across structural, chemical, and

Multilingual Idioms in Sentences and Conversations Across High-, Medium-, and Low-Resource Languages

arXiv:2606.02147v1 Announce Type: cross Abstract: Idiomatic expressions pose a major challenge for multilingual NLP because their meanings shift between figurative and literal usage, often requiring c

MURMUR: An Efficient Inference System for Long-Form ASR

arXiv:2606.01483v1 Announce Type: cross Abstract: Long-form automatic speech recognition (ASR) requires both high accuracy and low latency, but existing systems force a trade-off between the two. Chun