Search: “context”

@GaryMarcus has won again.😂 (I'm from Hong Kong, so the pictures are in Traditional Chinese)

This post from Gary Marcus appears to reference a humorous or notable moment related to his work, with image attachments in Traditional Chinese that provide context to the claim that he 'has won again

safetygary-marcus--x

24 May 2026

Human

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Model Releases

Integrable Elasticity via Neural Demand Potentials

DGX agent

arXiv:2605.22820v1 Announce Type: new Abstract: We propose the Integrable Context-Dependent Demand Network (ICDN), a demand-first neural model for multiproduct retail demand. The model learns log-dema

model-releasesarxiv-cs-lg

23 May 2026

From TF-IDF to Transformers: A Comparative and Ensemble Approach to Sentiment Classification

arXiv:2605.22003v1 Announce Type: new Abstract: Sentiment analysis, also referred to as opinion mining, primarily tries to extract opinion from any text-based data. In the context of movie reviews and

researcharxiv-cs-cl

22 May 2026

Build a Coding Assistant with Weaviate MCP: RAG over Code & Docs

This guide demonstrates how to build a coding assistant using Weaviate's Model Context Protocol (MCP) integration, enabling retrieval-augmented generation (RAG) capabilities over codebases and documen

model-releasesweaviate

JUDO: A Juxtaposed Domain-Oriented Multimodal Reasoner for Industrial Anomaly QA

model-releasesarxiv-cs-cv

arXiv:2605.20284v1 Announce Type: new Abstract: Industrial anomaly detection has been significantly advanced by Large Multimodal Models (LMMs), enabling diverse human instructions beyond detection, pa

Large-Step Training Dynamics of a Two-Factor Linear Transformer Model

model-releasesarxiv-cs-lg

arXiv:2605.21292v1 Announce Type: cross Abstract: Gradient-flow analyses show that simplified linear transformers can learn the in-context linear-regression algorithm, but they do not explain the fini

Pixel Wised Lesion Prediction on COVID-19 CT Imagery: A Comparative Analysis of Automated Image Segmentation Architectures

arXiv:2605.20459v1 Announce Type: new Abstract: In recent years, there has been a notable increase in the level of attention that is given to algorithms based on deep learning in the context of medica

researcharxiv-cs-cv

Agents

1Password extends OpenAI collaboration with Codex MCP server for just-in-time credential access

Cybersecurity and password service provider 1Password LLC today expanded its collaboration with OpenAI Group PBC, releasing a Model Context Protocol server that lets the Codex coding agent pull creden

agentssiliconangle

Tutorials

DOTRAG: Retrieval-Time Reasoning Along Paths

arXiv:2605.18760v1 Announce Type: cross Abstract: Graph Retrieval-Augmented Generation (GraphRAG) is dominated by a retrieve-then-reason paradigm, where context is retrieved using heuristics and then

tutorialsarxiv-cs-ai

Evaluating the Utility of Personal Health Records in Personalized Health AI

arXiv:2605.18937v1 Announce Type: new Abstract: Patient-managed Personal Health Records (PHRs) promises to empower patients to better understand their health; but information in the record is complex,

Eyes on VLM: Benchmarking Gaze Following and Social Gaze Prediction in Vision Language Models

arXiv:2605.19859v1 Announce Type: new Abstract: Vision-language models (VLMs) have rapidly evolved into general-purpose multimodal reasoners with strong zero-shot generalization. In this context, VLMs

researcharxiv-cs-cv

Safe Continual Reinforcement Learning under Nonstationarity via Adaptive Safety Constraints

arXiv:2605.18842v1 Announce Type: new Abstract: Safe reinforcement learning in nonstationary environments requires safety mechanisms that adapt as environmental conditions change. Standard safe reinfo

safetyarxiv-cs-lg

Boundedly Rational Meta-Learning in Sequential Consumer Choice

model-releasesarxiv-cs-lg

arXiv:2605.16532v1 Announce Type: new Abstract: Many consumer decisions are repeated choices under uncertainty. Standard models capture these decisions using Bayesian learning and dynamic programming:

Causal Intervention-Based Memory Selection for Long-Horizon LLM Agents

arXiv:2605.17641v1 Announce Type: new Abstract: Long-horizon LLM agents rely on persistent memory to support interactions across sessions, yet existing memory systems often retrieve context using sema

CompactAttention: Accelerating Chunked Prefill with Block-Union KV Selection

model-releasesarxiv-cs-cl

arXiv:2605.16839v1 Announce Type: new Abstract: Chunked prefill has become a widely adopted serving strategy for long-context large language models, but efficient attention computation in this regime

extsc{PrivScope}: Task-scoped Disclosure Control for Hybrid Agentic Systems

arXiv:2605.16630v1 Announce Type: cross Abstract: Hybrid local--cloud agents enrich user requests with context from persistent working state before delegating capability-intensive subtasks to a cloud

Agents

Fixed External Cameras as Common Prior Maps for Active 3D Scene Graph Generation

arXiv:2605.18184v1 Announce Type: cross Abstract: Commonly available prior information, such as BIM models, floor plans, and remote sensing images, can provide valuable geometric and semantic context

agentsarxiv-cs-ai

Local Ai

From Volume to Value: Preference-Aligned Memory Construction for On-Device RAG

arXiv:2605.18271v1 Announce Type: cross Abstract: With the rapid emergence of personal AI agents based on Large Language Models (LLMs), implementing them on-device has become essential for privacy and

local-aiarxiv-cs-ai

OSCAR: Offline Spectral Covariance-Aware Rotation for 2-bit KV Cache Quantization

arXiv:2605.17757v1 Announce Type: cross Abstract: INT2 KV-cache quantization is attractive for long-context LLM serving, but it remains difficult to make both accurate and deployable. Simple rotations

Recall Isn't Enough: Bounding Commitments in Personalized Language Systems

arXiv:2605.16712v1 Announce Type: new Abstract: Long-context and memory systems usually treat personalization as a recall problem. In practice, many failures occur later, when a system commits: it tur

SE-GA: Memory-Augmented Self-Evolution for GUI Agents

model-releasesarxiv-cs-lg

arXiv:2605.16883v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents often struggle with multi-step tasks due to constrained context windows and static policies that fail t

Hardware

TriAxialKV: Toward Extreme Low-Precision KV-Cache Quantization for Agentic Inference Tasks

arXiv:2605.17170v1 Announce Type: new Abstract: Agentic workloads have emerged as a major workload for LLM inference. They differ significantly from chat-only workloads, requiring long-context process

hardwarearxiv-cs-lg

Hardware

VeriCache: Turning Lossy KV Cache into Lossless LLM Inference

arXiv:2605.17613v1 Announce Type: cross Abstract: The large size of the KV cache has become a major bottleneck for serving LLMs with increasing context lengths. In response, many KV cache compression

hardwarearxiv-cs-lg

Visual Agentic Memory: Enabling Online Long Video Understanding via Online Indexing, Hierarchical Memory, and Agentic Retrieval

arXiv:2605.16481v1 Announce Type: cross Abstract: Long video understanding requires more than large context windows. It also needs a memory mechanism that decides what visual evidence to retain, keeps

WhiteTesseract: Reframing the Interpretation of Cultural Heritage through XR and Conversational AI

arXiv:2605.16972v1 Announce Type: cross Abstract: Cultural heritage exhibitions often struggle to sustain attention and support reflective engagement. Physical exhibitions rely on fixed interpretive a

Tools

as much as you spec there are always still ambiguities and unknown unknowns that come up and this gives the model a good out to make decisio…

I cannot provide an accurate summary of this entry as the title appears to be truncated mid-sentence and lacks sufficient context. Based on the incomplete title, it likely discusses how software speci

toolsthariq--x

18 May 2026

SMMBench: A Benchmark for Source-Distributed Multimodal Agent Memory

model-releasesarxiv-cs-cl

arXiv:2605.15710v1 Announce Type: new Abstract: Existing benchmarks for multimodal memory reasoning largely evaluate systems within pre-assembled contexts, but under-evaluate whether agents can use ev

18 May 2026

Head Forcing: Long Autoregressive Video Generation via Head Heterogeneity

arXiv:2605.14487v1 Announce Type: cross Abstract: Autoregressive video diffusion models support real-time synthesis but suffer from error accumulation and context loss over long horizons. We discover

PolitNuggets: Benchmarking Agentic Discovery of Long-Tail Political Facts

arXiv:2605.14002v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) embedded in agentic frameworks have transformed information retrieval from static, long context question answering into op

Hardware

SurgicalMamba: Dual-Path SSD with State Regramming for Online Surgical Phase Recognition

arXiv:2605.14889v1 Announce Type: cross Abstract: Online surgical phase recognition (SPR) underpins context-aware operating-room systems and requires committing to a prediction at every frame from pas

hardwarearxiv-cs-ai

Sycophancy is an Educational Safety Risk: Why LLM Tutors Need Sycophancy Benchmarks

arXiv:2605.14604v1 Announce Type: new Abstract: This position paper argues that effective tutoring requires corrective friction: surfacing misconceptions and challenging them supportively to drive con

When Evidence Conflicts: Uncertainty and Order Effects in Retrieval-Augmented Biomedical Question Answering

arXiv:2605.14115v1 Announce Type: new Abstract: Biomedical retrieval-augmented large language models (LLMs) often face evidence that is incomplete, misleading, or internally contradictory, yet evaluat

researcharxiv-cs-cl

A Unified Framework for Critical Scaling of Inverse Temperature in Self-Attention

arXiv:2605.12697v1 Announce Type: cross Abstract: Length-dependent logit rescaling is widely used to stabilize long-context self-attention, but existing analyses and methods suggest conflicting invers

researcharxiv-cs-lg

Humanwashing -- It Should Leave You Feeling Dirty

arXiv:2605.13723v1 Announce Type: cross Abstract: The phrase 'human in the loop' is increasingly used to imply a sense of safety in relation to AI decision systems. It shouldn't. There are contexts wh

safetyarxiv-cs-ai

Respecting Self-Uncertainty in On-Policy Self-Distillation for Efficient LLM Reasoning

arXiv:2605.13255v1 Announce Type: new Abstract: On-policy self-distillation trains a reasoning model on its own rollouts while a teacher, often the same model conditioned on privileged context, provid

safetyarxiv-cs-ai

Applications

Towards Robust Federated Multimodal Graph Learning under Modality Heterogeneity

arXiv:2605.12584v1 Announce Type: cross Abstract: Recently, multimodal graph learning (MGL) has garnered significant attention for integrating diverse modality information and structured context to su

applicationsarxiv-cs-ai

Uncovering Symmetry Transfer in Large Language Models via Layer-Peeled Optimization

arXiv:2605.12756v1 Announce Type: cross Abstract: Large language models (LLMs) are pretrained by minimizing the cross-entropy loss for next-token prediction. In this paper, we study whether this optim

Anti-Self-Distillation for Reasoning RL via Pointwise Mutual Information

arXiv:2605.11609v1 Announce Type: cross Abstract: On-policy self-distillation, where a student is pulled toward a copy of itself conditioned on privileged context (e.g., a verified solution or feedbac

safetyarxiv-cs-cl

13 May 2026

Agents

Beyond Manual Curation: Augmenting Targeted Protein Degradation Databases via Agentic Literature Extraction Workflows

arXiv:2605.11221v1 Announce Type: cross Abstract: Predictive models in biomedicine depend on structured assay data locked in the text, tables, and supplements of primary publications. This bottleneck

agentsarxiv-cs-lg

13 May 2026

💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter …

model-releasestogether-ai--x

💡 Why did @togethercompute choose NVIDIA Blackwell to serve DeepSeek-V4? Because NVIDIA Blackwell is built for the bottlenecks that matter most in long-context inference: → KV-cache pressure during de

13 May 2026

Key-Value Means

arXiv:2605.09877v1 Announce Type: cross Abstract: We present Key-Value Means ('KVM'), a novel block-recurrence for attention that can accommodate either fixed-size or growing state. Equipping a strong

On-Policy Distillation with Best-of-N Teacher Rollout Selection

arXiv:2605.09725v1 Announce Type: new Abstract: On-policy distillation (OPD), which supervises a student on its own sampled trajectories, has emerged as a data-efficient post-training method for impro

safetyarxiv-cs-cv

Priming: Hybrid State Space Models From Pre-trained Transformers

arXiv:2605.08301v1 Announce Type: cross Abstract: Hybrid State-Space models combine Attention with recurrent State-Space Model (SSM) layers, balancing eidetic memory from Attention with compressed fad

RDKV: Rate-Distortion Bit Allocation for Joint Eviction and Quantization of the KV Cache

arXiv:2605.08317v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance across diverse tasks, but their inference with long input contexts is bottlenecked by memor

Recursive Language Models

arXiv:2512.24601v3 Announce Type: replace Abstract: We study allowing large language models (LLMs) to process arbitrarily long prompts through the lens of inference-time scaling. We propose Recursive

Remember to Forget: Gated Adaptive Positional Encoding

arXiv:2605.10414v1 Announce Type: new Abstract: Rotary Positional Encoding (RoPE) is widely used in modern large language models. However, when sequences are extended beyond the range seen during trai

safetyarxiv-cs-lg

Adaptive Memory Decay for Log-Linear Attention

arXiv:2605.06946v1 Announce Type: cross Abstract: Sequence models face a fundamental tradeoff between memory capacity and computational efficiency. Transformers achieve expressive context modeling at

11 May 2026

Direction-Flipped Influence Audits Reveal Hidden Structure in Moral Choices of LLMs