Search: “llm”

KMGen: A Skill-based Approach for Synthetic Individual Patient Data Generation

model-releasesarxiv-cs-lg

arXiv:2608.22618v1 Announce Type: new Abstract: Individual patient data (IPD) from clinical trials is the substrate for survival modeling, meta-analysis, and safety research, yet IPD is rarely release

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Research

LanGuSTE: Language-Guided Coarse-to-Fine Patch Selection for Efficient Whole Slide Image Analysis

DGX agent

arXiv:2508.14537v2 Announce Type: replace Abstract: Whole slide images (WSIs) in computational pathology pose a major computational challenge due to their gigapixel scale, often requiring tens to hund

researcharxiv-cs-cv

25 Aug 2026

LitReview Arena: Evaluating Literature Review Agents with Battle-Style Peer Review Platform

arXiv:2608.21374v1 Announce Type: new Abstract: Literature reviews are essential to scientific progress, but rigorously evaluating automatically generated reviews remains difficult because many aspect

Meta-Ctrl: Guaranteed Plan Generation by Decoupling Syntactic and Semantic Constraints

arXiv:2608.22149v1 Announce Type: cross Abstract: LLMs generate fluent plans for robots but routinely violate the syntactic and se8mantic constraints they must satisfy to execute, and existing remedie

Tutorials

Mitigating Database Leakage in RAG Systems with Keyword-Grounded Fact Substitution

arXiv:2608.21656v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for combining large language models (LLMs) with external knowledge sources. Howe

tutorialsarxiv-cs-cl

Multimodal-Language-Model-Driven Interaction and Companionship for Service Robots in Elderly-Care Facilities

arXiv:2608.21387v1 Announce Type: new Abstract: Service robots are increasingly deployed in elderly-care facilities to alleviate caregiver workload and enhance the quality of daily care. However, most

safetyarxiv-cs-ro

No One Model Catches Every Harm: Benchmarking Content Moderation Across Safety Scenarios

arXiv:2608.21775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in real-world applications, yet they remain vulnerable to generating harmful content. From advers

safetyarxiv-cs-cl

On Predicting Vulnerability Severity Using In-Context Learning: An Industrial Case Study

arXiv:2608.22089v1 Announce Type: cross Abstract: Modern software systems require earlier and more scalable vulnerability severity assessment to reduce exposure to high-impact security flaws. Security

On the Role of Citations in Preference Data

arXiv:2608.21376v1 Announce Type: cross Abstract: Many NLP tasks require systems to provide attribution in their outputs--i.e. citations to grounding sources. Attribution serves as a bulwark against m

Open models, open science. Qwen keeps growing steadily, and we'll always be right here with the research community.🙌 Thanks for the deep di…

Open models, open science. Qwen keeps growing steadily, and we'll always be right here with the research community.🙌 Thanks for the deep dive! @natolambert Over the weekend I had Codex parse 500K arXi

model-releasesqwen--x

RetroDFM-R: Reasoning-Driven Retrosynthesis Prediction with Large Language Models via Reinforcement Learning

arXiv:2507.17448v2 Announce Type: replace-cross Abstract: Retrosynthetic planning is a cornerstone of organic synthesis and drug discovery. Yet existing AI methods often rely on pattern matching rathe

SAVER: Selective Auditing of Verbal Evidence for Error Recovery in VLM Change Reasoning

arXiv:2608.22857v1 Announce Type: new Abstract: Vision-language models (VLMs) frequently fail at visual change reasoning, even when their vision encoders contain sufficient information. We observe tha

SecOPD: Mitigating Adaptive Prompt Injections by On-Policy Distillation

arXiv:2608.21500v1 Announce Type: cross Abstract: Prompt injection is listed as the #1 threat to AI agents. When an agent accesses external data from websites, files, or emails, an attacker may inject

Small Reasoning Models are Instruction Followers in Function Calling

arXiv:2608.22472v1 Announce Type: new Abstract: Function calling represents the core capability of agentic large language models (LLMs). Existing research has focused on enhancing LLMs function-callin

local-aiarxiv-cs-ai

Spyre-Accelerated Retrieval-Augmented Generation on IBM LinuxONE: A Cloud-Native Architecture for Secure, High-Throughput Enterprise AI Inference

arXiv:2608.21393v1 Announce Type: new Abstract: Running large language models inside enterprise environments has always bumped up against a practical wall: the data lives in one place, the AI horsepow

SynEHR: Joint Modeling Inter-visit Temporal Evolution and Intra-visit Clinical Structure for Longitudinal EHR Synthesis

arXiv:2608.21673v1 Announce Type: cross Abstract: Longitudinal electronic health records (EHRs) document patients' sequences of clinical visits over time, preserving the temporal evolution of disease

The Geometry of Low-Resource Language Representations

arXiv:2608.23358v1 Announce Type: new Abstract: The performance gap between low- and high-resource languages in LLMs is widely known, but it remains unclear which internal model factors drive these di

Towards Safer Social Media Platforms: Scalable and Performant Few-Shot Harmful Content Moderation Using Large Language Models

arXiv:2501.13976v2 Announce Type: replace-cross Abstract: The prevalence of harmful content on social media platforms poses significant risks to users and society, necessitating more effective and sca

Training Large Language Models to Reason in a Continuous Latent Space

arXiv:2412.06769v4 Announce Type: replace Abstract: Large language models (LLMs) are typically constrained to reason in the language space, where they express the reasoning process through a chain-of-

Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning

arXiv:2608.21898v1 Announce Type: new Abstract: Web agents promise to automate complex digital workflows, but their training remains limited by synthetic environments that look plausible while hiding

TSWAP: A Multilingual Retrieval-Augmented Thai Wellness Advisor

model-releasesarxiv-cs-cl

arXiv:2608.22917v1 Announce Type: new Abstract: We present TSWAP, a deployed eight-language conversational wellness advisor grounded, via retrieval-augmented generation, in a verified knowledge base o

WARP: Wasserstein-Aligned RAG for Population Opinions

arXiv:2608.22859v1 Announce Type: cross Abstract: RAG systems are increasingly used to summarize what large collections of documents say. A user asks 'What do people think about X?' and receives an an

What actually runs: a measurement study of language model placement and decode speed on the Apple Neural Engine

model-releasesarxiv-cs-lg

arXiv:2608.22110v1 Announce Type: new Abstract: We ask what gets a language model onto the Apple Neural Engine (ANE) and what makes it fast there, and we answer with three measurements. We sweep a 64-

Where Cognition Lives: Dissecting Emergent from Computed Function in a Minimal Complete Cognitive Architecture

arXiv:2608.22347v1 Announce Type: new Abstract: A cognitive architecture is more than the module that reasons: it must also decide how long to think and what deserves the effort. We built a minimal bu

AEGIS: Preventing Cross-Domain Resource Abuse in MCP

arXiv:2608.20481v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an open source JSON-RPC protocol that standardizes how large language models (LLMs) interact with external systems

Agents

An integrated diffusion-weighted imaging processing and interpretation platform for MR-guided radiotherapy

arXiv:2608.20519v1 Announce Type: cross Abstract: Background: Magnetic resonance imaging-guided linear accelerators (MR-Linacs) allow diffusion-weighted imaging (DWI) to be acquired at every treatment

agentsarxiv-cs-ai

Applications

Annoying side effect of all the AI bots on the site is that they are all “well-read” and therefore reply cogently my niche reference tweets …

applicationsethan-mollick--x

Annoying side effect of all the AI bots on the site is that they are all “well-read” and therefore reply cogently my niche reference tweets that would normally attract a small but interested group now

Approximate Homomorphisms and Convergent Representations in Transducers

arXiv:2608.20428v1 Announce Type: cross Abstract: We study the stability of minimal representations of controlled stochastic processes (in particular, transducers) under perturbations. This question i

local-aiarxiv-cs-ai

Agents

ARGUS: Theory-of-Mind Guided Argument Generation with Strategy-Aware Planning and Knowledge Grounding

arXiv:2608.20405v1 Announce Type: new Abstract: Persuasive argument generation requires modeling audience beliefs, rhetorical strategies, and factual grounding. Despite recent advancements, existing m

agentsarxiv-cs-cl

AsmEvo: Agentic Assembly-Level Optimization of AMD GPU Kernels with Functional Equivalence Verification

model-releasesarxiv-cs-cl

arXiv:2608.20711v1 Announce Type: new Abstract: High-performance ML systems increasingly rely on GPU kernels whose editable source is unavailable, generated, or too distant from final machine code to

Can Scientific Claims Be Removed from Large Language Models? A Systematic Evaluation of Claim-Level Unlearning

arXiv:2608.20960v1 Announce Type: new Abstract: Language models (LMs) are trained on static scientific corpora, whereas scientific knowledge continuously evolves through correction and revision. Scien

Clarify-Then-Search: A Clarification Benchmark for Deep Search with End-to-End Nugget Restoration

arXiv:2608.20357v1 Announce Type: cross Abstract: Deep search is brittle on underspecified user queries: missing constraints such as time, location, scope, or definitions can lead to retrieval drift a

CogCanvas: A Benchmark for Evaluating Multi-Subject Reference-Based Image Generation

model-releasesarxiv-cs-cv

arXiv:2606.15867v2 Announce Type: replace Abstract: Multi-subject reference-based image generation requires jointly preserving multiple human identities, binding per-person objects and fashion items,

Dynamic Context Scheduling: Learning Beyond the Static Universe

arXiv:2608.20799v1 Announce Type: new Abstract: We study dynamic context scheduling as a training instrument for contextual re- inforcement learning. Rather than treating intra-episode context variati

EnSI-RAG: Entity-Structure-Indexed Retrieval-Augmented Generation for Long-Document Question Answering

arXiv:2608.21252v1 Announce Type: cross Abstract: Question answering (QA) over long, connected documents remains challenging because relevant evidence may span multiple entities and their relationship

GPU issue

A month i setup a proxmox server using spare parts like a z270 i7 7700k and 2x8 2666 but since i don't have any hardware acceleration i was planning to pass down my rx 580 8GB to my server but i heard

local-air-ollama

Hadith computational science in the age of large language models: a critical narrative review

arXiv:2608.20364v1 Announce Type: cross Abstract: We examine how hadith computational science is being reshaped by transformer models, retrieval-grounded pipelines, and large language models (LLMs). R

Inhibitory Attention for Clinical Long-Context Reasoning: Characterizing and Mitigating Lost-in-the-Middle Effects in EHR Processing

arXiv:2608.20348v1 Announce Type: cross Abstract: Electronic health records now routinely exceed 100,000 tokens per patient. Yet large language models exhibit the lost-in-the-middle (LitM) effect: inf

Knowledge-Graph-Gated Defactualization for Style-Controllable and Fact-Preserving Generation in Agentic Conversational AI

arXiv:2608.20393v1 Announce Type: cross Abstract: Agentic large language models (LLMs) deployed in fact-sensitive applications such as customer support must simultaneously preserve factual correctness

Making Deployments Safe at Meta: Health Checks for Continuous Change-Safety

arXiv:2608.20513v1 Announce Type: cross Abstract: Continuous deployment to large scale production systems creates a tension between release velocity and reliability. Every change is a potential reliab

Memory Augmentation Unlocks Efficient Chain-of-Thought Reasoning

arXiv:2608.21265v1 Announce Type: new Abstract: Large language models often rely on Chain-of-Thought (CoT) reasoning to solve complex tasks, but verbose reasoning traces introduce substantial inferenc

MGAL: A Multilingual Granularity-Aware Long-Context Benchmark

arXiv:2608.20853v1 Announce Type: new Abstract: Evaluation of long-context Large Language Models (LLMs) has advanced rapidly. However, most existing benchmarks are limited to the document level and fo

Minimax raising rates 60%-65%

Minimax just announced (only over xhitter apparently) that it is raising rates by 60%-65% tomorrow, the 25th. If you use Minimax, you'll either want to lock in their current rates. Sadly, every chines

local-air-ollama

Qwen 27B 3.8 quants: How low can you go?

model-releasesr-localllama

For the GPU poor among us: I'm curious what results you're getting with low quants of Qwen 27B 3.8. My main inference hardware is limited (Mac mini M4 24 GB), but I'm getting great results with Unslot

qwen38-27b-rtx3090 (https://github.com/syv-ai/qwen38-27b-rtx3090) is extremely good with deepseek harness.

model-releasesr-localllama

With vision enabled I am able to run at 150k context on a single RTX 3090 and the results are just amazing. I was even able to write a gmail plugin for DeepSeek harness with locally hosted Qwen 3.8 27

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

arXiv:2608.21100v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimod

local-aiarxiv-cs-ai

Representation Affects Retrieval: A Case Study of Skill Discovery and Routing in a Multimodal Agent Harness

arXiv:2608.20389v1 Announce Type: new Abstract: A production agent harness must discover and rank, from a growing library of skills, the one most appropriate for a user's task. At small scale this sel

Agents

SDAD: Spec-Driven Agentic Development for the AI-Native SDLC

arXiv:2608.20341v1 Announce Type: new Abstract: Frontier coding agents backed by large language models with context windows from hundreds of thousands to millions of tokens are restructuring the Softw

agentsarxiv-cs-ai