Search: “context”

First, do no harm: Breaking suicidogenic echo chambers in media recommendation

arXiv:2605.25258v1 Announce Type: cross Abstract: Recommender systems generally optimises user engagement, but this approach is dangerous in mental health contexts. When vulnerable users show signs of

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From Facts to Insights: A Persona-Driven Dual Memory Framework and Dataset for Role-Playing Agents

DGX agent

arXiv:2605.25693v1 Announce Type: new Abstract: While role-playing agents excel in short-term interactions, long-term conversations overwhelm context windows, motivating external memory frameworks. Cu

model-releasesarxiv-cs-cl

26 May 2026

From Model Scaling to System Scaling: Scaling the Harness in Agentic AI

arXiv:2605.26112v1 Announce Type: new Abstract: This paper studies the next major bottleneck in agentic AI as system scaling, not only model scaling: the design of auditable, persistent, modular, and

Mistral-7B v0.3 at 128K in llama.cpp: 22,657 → 13,235 MiB live VRAM with ≤0.004 PPL drift

Mistral-7B v0.3 model achieves significant memory optimization when running at 128K context length in llama.cpp, reducing live VRAM usage from 22,657 MiB to 13,235 MiB while maintaining minimal perfor

model-releasesr-ollama

OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization

arXiv:2602.10635v2 Announce Type: replace Abstract: Socially intelligent AI systems must entail reasoning across diverse human behavioral tasks, and generalization to new contexts. However, AI has yet

Palette: A Modular, Controllable, and Efficient Framework for On-demand Authorized Safety Alignment Relaxation in LLMs

arXiv:2605.24154v1 Announce Type: new Abstract: Current safety alignment of foundation models largely follows a one-size-fits-all paradigm, applying the same refusal policy across users and contexts.

Poisoning the Watchtower: Prompt Injection Attacks Against LLM-Augmented Security Operations Through Adversarial Log Content

arXiv:2605.24421v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as analyst assistants in security operations centers (SOCs), where they ingest log and alert data t

Pragmatic Reasoning improves LLM Code Generation

arXiv:2502.15835v5 Announce Type: replace-cross Abstract: Pragmatic reasoning helps interlocutors infer intended meaning from ambiguous or underspecified messages by considering shared context and cou

PRIMA: Operational Patterns for Resilient Multi-Agent Research with Verifiable Identity and Convergent Feedback

arXiv:2605.24775v1 Announce Type: new Abstract: Operating LLMs as coordinated multi-agent research systems over multi-hour runs surfaces failure modes that single-shot evaluation cannot: upstream prov

agentsarxiv-cs-ai

Prism: Spectral-Aware Block-Sparse Attention

arXiv:2602.08426v2 Announce Type: replace-cross Abstract: Block-sparse attention is promising for accelerating long-context LLM pre-filling, yet identifying relevant blocks efficiently remains a bottl

researcharxiv-cs-ai

Retrieval as Reasoning: Self-Evolving Agent-Native Retrieval via LLM-Wiki

arXiv:2605.25480v1 Announce Type: new Abstract: LLM agents require retrieval to behave less like one-shot context fetching and more like reasoning: searching, reading, traversing, and deciding when ev

agentsarxiv-cs-cl

SliceWorld: A Predictive and Controllable World-State Model for CT Report Generation

arXiv:2605.24371v1 Announce Type: cross Abstract: CT report generation (CTRG) requires models to summarize three-dimensional anatomical context and pathological findings from hundreds of axial slices.

safetyarxiv-cs-cl

SPARK: Search Personalization via Agent-Driven Retrieval and Knowledge-sharing

arXiv:2512.24008v3 Announce Type: replace Abstract: Personalized search demands the ability to model users' evolving, multi-dimensional information needs; a challenge for systems constrained by static

agentsarxiv-cs-ai

Towards Long-Horizon Interpretability: Efficient and Faithful Multi-Token Attribution for Reasoning LLMs

arXiv:2602.01914v2 Announce Type: replace Abstract: Token attribution methods provide intuitive explanations for language model outputs by identifying causally important input tokens. However, as mode

When the Manual Lies: A Realistic Benchmark to Evaluate MCP Poisoning Attacks for LLM Agents

arXiv:2605.24069v1 Announce Type: cross Abstract: The rise of tool-using Large Language Model (LLM) agents, standardized by protocols like the Model Context Protocol (MCP), has unlocked unprecedented

A Simple Plug-in for Improving Eviction-Based KV Cache Compression

arXiv:2605.23258v1 Announce Type: new Abstract: KV cache growth is a major bottleneck for long-context inference in large language models. Existing methods are often dominated by binary eviction or re

Benchmarking Google Embeddings 2 against Open-Source Models for Multilingual Dense Retrieval and RAG Systems

arXiv:2605.23618v1 Announce Type: new Abstract: We benchmark Google Embeddings (GE2), a Vertex-AI-hosted bi-encoder with 2,048-token context and explicit task-type conditioning, against five open-sour

Built a local MCP memory server that uses Ollama to give AI coding assistants persistent memory — no cloud, no API keys, Tool and Model Agnostic

A developer created a local Model Context Protocol (MCP) memory server that integrates Ollama to provide AI coding assistants with persistent memory capabilities while maintaining complete privacy and

local-air-ollama

DFKI-MLT at SemEval-2026 TASK 7: Steering Multilingual Models Towards Cultural Knowledge

arXiv:2605.23069v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used across diverse linguistic and cultural contexts, yet their cultural knowledge remains uneven across r

/goal is really insane! It's how you can get the most out of coding agents today. For efficiency, I find it works best when you do planning …

/goal is really insane! It's how you can get the most out of coding agents today. For efficiency, I find it works best when you do planning before /goal. This ensures the agent has the right context a

agentsdair-ai--x

HawkesLLM: Semantic Uncertainty Propagation in Agentic Text Simulation

arXiv:2605.23043v1 Announce Type: new Abstract: Agentic text-simulation systems write in sequence, with each item becoming possible context for later steps. That makes uncertainty path-dependent: an e

local-aiarxiv-cs-cl

Applications

How Human-Like Are Large Language Models? A Register-Aware Linguistic Evaluation Framework

arXiv:2605.23651v1 Announce Type: new Abstract: While factual correctness and task-performance have been in focus of Large Language Model (LLM) research for a long time, the fundamental question of ho

applicationsarxiv-cs-cl

Learning Through Noise: Why Subliminal Learning Works and When It Fails

arXiv:2605.23645v1 Announce Type: cross Abstract: In the context of artificial neural networks, subliminal learning refers to the transfer of task-relevant knowledge or unintended biases from teacher

researcharxiv-cs-ai

Hardware

MiniCPM5-1B is an impressive release in the 1B class! @OpenBMB https://huggingface.co/collections/openbmb/minicpm5 ✨ 1B - Apache 2.0 ✨ Hybri…

MiniCPM5-1B is an impressive release in the 1B class! @OpenBMB https://huggingface.co/collections/openbmb/minicpm5 ✨ 1B - Apache 2.0 ✨ Hybrid reasoning with Think / No-Think modes ✨ 128K context ✨ Run

hardwareclem-delangue--x

Mitigating Object Hallucinations via Sentence-Level Early Intervention

arXiv:2507.12455v3 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have revolutionized cross-modal understanding but continue to struggle with hallucinations - fabricated con

researcharxiv-cs-cv

on this, @DavidSacks and I agree.

Gary Marcus and David Sacks found common ground on an unspecified topic, as indicated by Marcus's post on X (formerly Twitter). Without access to the full thread context, the specific point of agreeme

safetygary-marcus--x

Through the Stealth Lens: Attention-Aware Defenses Against Poisoning in RAG

arXiv:2506.04390v2 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems are vulnerable to attacks that inject poisoned passages into the retrieved context, even at low c

When Symptoms Are Not Enough: Evidence-Weighting Patterns in Large Language Model Psychiatric Screening

arXiv:2605.23148v1 Announce Type: new Abstract: As demand for mental health care outpaces clinician-delivered assessment, scalable screening tools are increasingly needed. Large language models (LLMs)

Agents shouldn’t have direct visibility into env vars or credentials that can expose sensitive systems and data. Keeping secrets outside the…

Agents shouldn’t have direct visibility into env vars or credentials that can expose sensitive systems and data. Keeping secrets outside the agent’s context helps secure the env while still allowing a

agentsharrison-chase--x

23 May 2026

b9297

local-aillama-cpp-releases

The search results show information about llama.cpp releases but don't contain specific details about build b9297. Based on the context and numbering (b9297 is a recent build after b9294), b9297 is li

23 May 2026

Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents

model-releasesarxiv-cs-lg

arXiv:2605.21768v1 Announce Type: new Abstract: Memory-augmented LLM agents enable interactions that extend beyond finite context windows by storing, updating, and reusing information across sessions.

23 May 2026

Code Researcher: Deep Research Agent for Large Systems Code and Commit History

arXiv:2506.11060v2 Announce Type: replace-cross Abstract: Large Language Model (LLM)-based coding agents have shown promising results on coding benchmarks, but their effectiveness on systems code rema

Tools

—dangerously-skip-git

This post likely discusses the `--dangerously-skip-git` flag or parameter, probably in the context of a framework or tool (possibly Remix or similar Swyx-related projects), explaining why this dangero

toolsswyx--x

Modeling Emotional Dynamics in Agent-to-Agent Interactions on Moltbook

arXiv:2605.20442v1 Announce Type: cross Abstract: Generative AI systems are increasingly deployed as interactive agents in online environments, such as a social network called Moltbook. In Moltbook, l

Modeling Pathology-Like Behavioral Patterns in Language Models Through Behavioral Fine-Tuning

arXiv:2605.22356v1 Announce Type: new Abstract: Large language models are increasingly used as computational tools for modeling human-like behavior. We introduce a behavioral induction framework that

safetyarxiv-cs-cl

Noise-Space Attribution and Control of Chunk-Boundary Artifact

arXiv:2603.11642v2 Announce Type: replace Abstract: Action chunking is widely used in generative visuomotor policies, yet the recurring execution discontinuities at chunk boundaries still lack a mecha

safetyarxiv-cs-ro

nope you are. because openai will sell your most private data to the government.

This post appears to express concerns about OpenAI's data privacy practices and potential government data sharing, though the claim lacks specific evidence or context. Gary Marcus, an AI researcher an

safetygary-marcus--x

Putnam 2025 Problems in Rocq using Opus 4.6 and Rocq-MCP

arXiv:2603.20405v2 Announce Type: replace-cross Abstract: We report on an experiment in which Claude Opus~4.6, equipped with a suite of Model Context Protocol (MCP) tools for the Rocq proof assistant,

Reducing Political Manipulation with Consistency Training

arXiv:2605.22771v1 Announce Type: new Abstract: Large language models (LLMs) exhibit systematic political bias across a variety of sensitive contexts. We find that LLMs handle counterpart topics from

safetyarxiv-cs-cl

using ltx 2.3 i2v 3d animation with reference voice using TalkVid Lora.

local-air-stablediffusion

ID-LoRA (Identity-Driven In-Context LoRA) enables identity-preserving audio-video generation by simultaneously dictating the scene's visual content, environmental acoustics, and speaking style while p

b9260

local-aillama-cpp-releases

Release b9260 of llama.cpp includes OpenCL backend refactoring that improves initialization, GPU identification, and performance by caching global memory size in device context. llama.cpp enables LLM

Industry

Be the zeitgeist.

industrycristobal-valenzuela--x

This post likely discusses strategies for creating or embodying cultural relevance and capturing the spirit of the times, possibly in the context of technology, AI, or creative work. The author, Crist

CIG: Exploration via Conditional Information Gain

arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated

Compositional Transduction with Latent Analogies for Offline Goal-Conditioned Reinforcement Learning

arXiv:2605.20609v1 Announce Type: new Abstract: Compositional generalization is essential for reaching unseen goals under novel contextual variations in offline goal-conditioned reinforcement learning

agentsarxiv-cs-lg

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning

arXiv:2605.20385v1 Announce Type: new Abstract: Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the

researcharxiv-cs-cv

DySink: Dynamic Frame Sinks for Autoregressive Long Video Generation

model-releasesarxiv-cs-cv

arXiv:2605.21028v1 Announce Type: new Abstract: Autoregressive long video generation often adopts bounded-memory streaming for efficiency, typically combining local windows for short-term continuity w

Fast and Stable Triangular Inversion for Delta-Rule Linear Transformers

arXiv:2605.21325v1 Announce Type: new Abstract: Linear attention has emerged as a cornerstone for efficient long-context architectures, as evidenced by its integration into state-of-the-art open-sourc

Tutorials

How to build LLM-as-a-Judge evaluators that hold up in production

Learn how to design, calibrate, and run LLM-as-a-judge evaluators with fixed labels, human agreement checks, trace context, and Phoenix Evals. The post How to build LLM-as-a-Judge evaluators that hold

tutorialsarize-ai