Search: “context”

Hypotheses-Guided Self Distillation for Continual Personalization

arXiv:2609.00251v1 Announce Type: new Abstract: As people increasingly interact with LLM assistants in daily life, continually adapting to individual preferences has become essential for effective lon

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Inspicio: Open-Vocabulary, LLM-Based Sense Retrieval for Historical Languages

DGX agent

arXiv:2609.00998v1 Announce Type: cross Abstract: Word Sense Disambiguation has advanced rapidly for English and a handful of well-resourced modern languages, but it continues to assume the existence

researcharxiv-cs-ai

2 Sept 2026

Instella-MoE Technical Report

arXiv:2609.00791v1 Announce Type: cross Abstract: In this work, we introduce Instella-MoE, a fully open Mixture-of-Experts (MoE) language model with 16 billion total parameters and 2.8 billion active

Learning Sparse Decision Trees via Transformer Variational Auto-Encoders

arXiv:2609.01430v1 Announce Type: cross Abstract: Decision trees are among the most widely used models in machine learning, largely due to their transparent decision logic, making them well-suited for

Life Operators: a self-evolving framework for multiscale life modelling

arXiv:2609.00068v1 Announce Type: cross Abstract: Medical AI is moving beyond recognition towards clinical dialogue and longitudinal prediction. Yet a central question remains: how would a patient's s

local-aiarxiv-cs-ai

Location-Aware Language Models via Secondary Embeddings

arXiv:2609.00454v1 Announce Type: new Abstract: Pretrained transformer-based language models achieve strong performance across a wide range of NLP tasks but remain limited in encoding geo-locational s

safetyarxiv-cs-cl

Measuring consistency via ensemble margin and local prediction variability: Auditing decision systems in the presence of predictive multiplicity

arXiv:2609.01397v1 Announce Type: cross Abstract: The Rashomon effect is a machine learning phenomenon where equally accurate models produce different predictions for the same inputs (predictive multi

Membership Inference in Fine-tuned Diffusion Language Models via Token-level Memorization Asymmetry

arXiv:2609.00873v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as an alternative modeling paradigm to autoregressive LMs, offering advantages such as parallel g

Multilingual Medical Reasoning for Question Answering with Large Language Models

arXiv:2512.05658v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) with reasoning capabilities have recently demonstrated strong potential in medical Question Answering (QA). Exist

On the Design Fundamentals of Pixel Text Representation Learning

arXiv:2609.01147v1 Announce Type: cross Abstract: Text-rich visual inputs require models that can read, retrieve, and compress language directly in pixel space, yet existing pixel-text encoders strugg

safetyarxiv-cs-cl

OUTLETS: Output-Length Prediction from Speculative Decoding Backbones

arXiv:2609.01068v1 Announce Type: new Abstract: The heavy-tailed distribution of output lengths in Large Language Model (LLM) serving poses major challenges for resource provisioning and cluster sched

P-PatchDiff: Progressive Patch Diffusion Models for Low-light Image Enhancement

arXiv:2609.01123v1 Announce Type: new Abstract: Recent advancements in low-light image enhancement have leveraged diffusion models for their strong ability to generate perceptually realistic, detailed

local-aiarxiv-cs-cv

Pix2Rep-v2: Data-Efficient Representation Learning for Dense Medical Imaging Applications

arXiv:2609.01427v1 Announce Type: new Abstract: Dense self-supervised learning (SSL) is a powerful paradigm for learning without annotations the local descriptors required to solve dense medical imagi

researcharxiv-cs-cv

Agents

Polished but Unresolved: Identifying Late-Stage Pressure States in Long-Horizon Tool-Use Agents

arXiv:2609.00823v1 Announce Type: new Abstract: Long-horizon tool-use agents need not only to search and plan, but also to decide when to finalize. We study late-stage pressure states, in which an age

agentsarxiv-cs-ai

Tutorials

PredErase: Training-Free Object-and-Effect Removal with Predictive Latent Guidance

arXiv:2609.00956v1 Announce Type: new Abstract: Removing an object is not the same as filling its mask. Cast shadows and contact shading usually lie outside the user-provided instance mask M_obj, so a

tutorialsarxiv-cs-cv

Probing Factual Knowledge Transfer with Training Data Interventions

arXiv:2609.01341v1 Announce Type: cross Abstract: Do multilingual language models transfer factual knowledge across languages during continued pretraining, or do they mostly recall facts learned direc

Prompt-Robust Language Models: Which Training Strategies Work?

arXiv:2609.01217v1 Announce Type: new Abstract: Despite their strong performance, large language models remain highly sensitive to prompt formulation. Prior work addresses this through refined data co

Pulled the trigger, RIP $6,279

model-releasesr-stablediffusion

(Paid 5,849 + tax, which came out to 6,279) TL;DR - Bought this 5090 prebuilt and I want to sanity check if I made the right decision and at the right time. Hey everyone. So I want to start off by say

Quit While You're Ahead: Quit for Efficient Candidate Generation in Machine Translation Reranking

arXiv:2609.00588v1 Announce Type: new Abstract: Reranking methods, such as Minimum Bayes Risk (MBR) decoding and Quality Estimation (QE) reranking, are widely used in modern neural machine translation

RecalibrateGPT: AI Fatigue Resilient Conversational Interfaces

arXiv:2609.00506v1 Announce Type: cross Abstract: Large language models are powerful, but their interfaces often devolve into a type rightarrow read rightarrow retype loop, creating conversational AI

Reliability Challenges in Diffusion Vision-Language Models

arXiv:2609.01318v1 Announce Type: cross Abstract: Diffusion-based Large Vision-Language Models (dLVLMs) have recently emerged as a compelling alternative to autoregressive (AR) LVLMs, offering advanta

safetyarxiv-cs-cl

Replacing Training with Memory: Listwise Selection for Text-to-SQL

arXiv:2609.00834v1 Announce Type: cross Abstract: Modern Text-to-SQL systems often follow generate-execute-select pipelines, generating multiple candidate queries then selecting the best one. Listwise

RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation

arXiv:2609.00918v1 Announce Type: new Abstract: Large language models are increasingly used as interactive recommender assistants. Their evaluation should therefore go beyond plausible item recommenda

SAGE: State-Grounded, Abstention-Aware Evaluation of Task-Oriented Dialogue Agents

arXiv:2609.00434v1 Announce Type: new Abstract: Evaluating task-oriented dialogue agents requires judging not merely whether a reply reads well but whether each turn advances the underlying workflow s

Same Semantics, Different Outcome: On the Modality Robustness of Multimodal LLMs under Knowledge Conflict

arXiv:2609.00550v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly provided with contextual evidence in heterogeneous forms: as a text passage, as a rendered ima

Scaled Idempotence in Transformer Attention: Paired OV Geometry and Shared-Value Algebras

arXiv:2609.01129v1 Announce Type: new Abstract: We identify a recurrent algebraic regularity in Transformer attention: a sparse subset of effective OV operators T=OV^op nearly closes under composition

safetyarxiv-cs-lg

SeerGuard: A Safety Framework for Mobile GUI Agents via World Model Prediction

arXiv:2607.15550v2 Announce Type: replace Abstract: Mobile graphical user interface (GUI) agents have demonstrated remarkable capabilities in automating complex tasks, yet they introduce critical safe

SMELT: Scaling Laws for Compute-Matched MoE Looped Transformers

arXiv:2609.01343v1 Announce Type: new Abstract: Looped Transformers increase effective depth by iterating a shared block of layers, but most evaluations compare at fixed model size, conflating archite

safetyarxiv-cs-lg

StreamScout: Learning When to Look Deeper for Streaming Video Understanding

arXiv:2609.00291v1 Announce Type: new Abstract: Streaming video understanding requires answering questions that arrive at arbitrary moments over an unbounded video stream. Existing systems primarily f

safetyarxiv-cs-cv

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

arXiv:2609.00787v1 Announce Type: new Abstract: Humans need to study only a handful of well-written textbooks to master a discipline and attempt its hardest problems. We argue that an ideal self-evolu

TempCloze: Can Video-LLMs Identify the Missing Middle?

arXiv:2609.01515v1 Announce Type: cross Abstract: Temporal reasoning benchmarks for Video-LLMs are often mediated by language, leaving room for linguistic shortcuts from option wording, answer correla

Think Like a Doctor: Conversational Diagnosis through the Exploration of Diagnostic Knowledge Graphs

arXiv:2602.01995v2 Announce Type: replace Abstract: Conversational diagnosis requires multi-turn history-taking, where an agent asks clarifying questions to refine differential diagnoses under incompl

Today we’re open-sourcing Lily, the local inference engine we built for hybrid compute in Perplexity Computer. Lily is specialized for Qwen3…

Today we’re open-sourcing Lily, the local inference engine we built for hybrid compute in Perplexity Computer. Lily is specialized for Qwen3.6-35B-A3B on Apple silicon, built so on-device compute does

local-aiperplexity--x

TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2609.00832v1 Announce Type: new Abstract: The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery. In this contex

UI-VISA: U-Net Initialized Vascular Image Segmentation Architecture

arXiv:2609.01598v1 Announce Type: new Abstract: Accurate segmentation of vascular structures in digital subtraction angiography (DSA) images remains challenging due to the thin, elongated, and branchi

researcharxiv-cs-cv

VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferences

arXiv:2609.00921v1 Announce Type: new Abstract: Personalized Large Language Models (PLLMs) aim to tailor responses to individual users, where a central challenge is preference reasoning: inferring que

Visual Attention Faithfulness in Vision-Language Models is Heterogeneous

arXiv:2609.00830v1 Announce Type: cross Abstract: Whether attention weights faithfully reflect model reasoning has been actively debated in NLP, yet this question remains largely unexplored for the vi

local-aiarxiv-cs-ai

When Compression Helps and When It Hurts: Condition-Aware Analysis of Chain-of-Thought Distillation

arXiv:2606.21704v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) distillation transfers multi-step reasoning from large reasoning models to smaller students, but verbose teacher traces infla

A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction

arXiv:2608.29705v1 Announce Type: cross Abstract: Feed-forward 3D reconstruction models emit a per-pixel confidence that downstream systems read as a reliability signal. It is trained as a loss weight

Agents

A Human-in-the-Loop Autonomous Agent for Industry Time Series Forecasting

arXiv:2608.30976v1 Announce Type: new Abstract: Real-world time-series forecasting is rarely a one-shot model invocation: practitioners must formulate tasks, connect data and models, incorporate domai

agentsarxiv-cs-lg

A Study of the Design Space of Motion and Disocclusion Control in Video Generation

model-releasesarxiv-cs-cv

arXiv:2512.13392v3 Announce Type: replace Abstract: Disocclusion occurs when object movement reveals previously hidden content. Existing image-to-video methods provide different forms of motion and di

A^2Agent: Action-Aware Reinforcement Learning for Repository-Level Code Localization Agents

arXiv:2608.29831v1 Announce Type: new Abstract: Localizing issue-relevant code regions is a critical step in automated software engineering. However, due to their reliance on sparse trajectory-level s

local-aiarxiv-cs-cl

AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs

arXiv:2601.06022v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit complementary strengths arising from differences in pretraining data, model architectures, and decoding b

Applications

AdapToPASS: Ambiguity-aware Adaptive Spherical Transformer for Panoramic Semantic Segmentation

arXiv:2608.29081v1 Announce Type: new Abstract: Spherical Transformers have emerged as a promising framework for panoramic semantic segmentation (PASS) by operating directly on spherical geometry and

applicationsarxiv-cs-cv

AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing

arXiv:2608.29622v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs), yet existing RAG systems often struggle with complex, mu

All currently popular local models in one table + Opus 4.8 results

model-releasesr-localllama

If you are thinking what model will fit best your HW specs and tasks you are doing here is one table with all currently popular models that still can be considered as local. LLM Test Scores Feature De

Annotated Surrogate Retrieval for Polish Statutory Law

model-releasesarxiv-cs-cl

arXiv:2608.30929v1 Announce Type: new Abstract: We present a family of retrieval methods for Polish statutory law built on document surrogates: language-model annotations attached to statutory article

Answer Bubbles: Information Exposure in AI-Mediated Search

arXiv:2603.16138v2 Announce Type: replace-cross Abstract: Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these sys