Search: “llm”

CLFEC: A New Task for Unified Linguistic and Factual Error Correction in paragraph-level Chinese Professional Writing

arXiv:2602.23845v2 Announce Type: replace Abstract: Chinese text correction has traditionally focused on spelling and grammar, while factual error correction is usually treated separately. However, in

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Continual Learning Bench: Evaluating Frontier AI Systems in Real-World Stateful Environments

DGX agent

arXiv:2606.05661v1 Announce Type: cross Abstract: Continual learning, the ability of AI systems to improve through sequential experience, has attracted substantial interest, but no high-quality benchm

model-releasesarxiv-cs-cl

5 Jun 2026

Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation

arXiv:2606.05290v1 Announce Type: new Abstract: Recent progress in generative modeling has made safety control a central challenge, yet existing approaches remain largely model-specific, requiring ret

safetyarxiv-cs-cv

DocHop-QA: Towards Multi-Hop Reasoning over Multimodal Document Collections

arXiv:2508.15851v2 Announce Type: replace Abstract: Despite rapid progress in large language models (LLMs), current QA benchmarks still overlook the core challenge of real-world scientific information

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

Agents

Harnessing Generalist Agents for Contextualized Time Series

arXiv:2606.05404v1 Announce Type: cross Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling. Moreover, real-world practitioners often require end-to-end

agentsarxiv-cs-cl

IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization

arXiv:2407.10486v3 Announce Type: replace-cross Abstract: Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and pe

IR3DE: A Linear Router for Large Language Models

arXiv:2606.06098v1 Announce Type: new Abstract: Foundational Large Language Models (LLMs) demonstrate proficiency on a wide range of general tasks, and achieve remarkable results on various specialize

Latent Reasoning with Normalizing Flows

arXiv:2606.06447v1 Announce Type: new Abstract: Large language models often improve reasoning by generating explicit chain-of-thought (CoT), demonstrating the importance of intermediate computation. H

MAviS: A Multimodal Conversational Assistant For Avian Species

model-releasesarxiv-cs-cv

arXiv:2603.07294v2 Announce Type: replace Abstract: Fine-grained understanding and species-specific multimodal question answering are vital for advancing biodiversity conservation and ecological monit

MIRAI: Prediction and Generation of High-Impact Academic Research

arXiv:2606.05443v1 Announce Type: cross Abstract: The rapid pace of scientific publishing has made the identification and synthesis of high-impact work an increasingly urgent challenge. We introduce M

NAVIRA: Decoupled Stochastic Remasking for Masked Diffusion Language Models

arXiv:2606.06031v1 Announce Type: new Abstract: Masked diffusion language models generate text by iteratively unmasking many tokens in parallel, but this speed comes with a correction problem: tokens

local-aiarxiv-cs-cl

On Advantage Estimates for Max@K Policy Gradients

arXiv:2606.06080v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards is widely used for post-training reasoning models, but sparse outcome rewards make exploration difficul

Applications

OneReason Technical Report

arXiv:2606.06260v1 Announce Type: cross Abstract: Generative recommendation models in the OneRec family have been widely deployed in many real-world services, such as short-video, live-streaming, adve

applicationsarxiv-cs-cl

OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation

arXiv:2606.06096v1 Announce Type: cross Abstract: Policy-gradient methods usually optimize expected return, but many real world applications care about distributional properties of returns: tail risk,

ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models

arXiv:2601.02880v2 Announce Type: replace-cross Abstract: Every existing inference-time reasoning framework discards all failure context at problem boundaries, leaving a model solving problem 500 no w

Scaffold, Not Vocabulary? A Controlled, Two-Tier, Pre-Registered Study of a Popperian Code-Generation Skill

arXiv:2606.06454v1 Announce Type: cross Abstract: Large language models increasingly write, review, and judge code, and a fast-growing practice equips them with prompt 'skills' that ask the model to r

TARPO: Token-Wise Latent-Explicit Reasoning via Action-Routing Policy Optimization

arXiv:2606.05859v1 Announce Type: new Abstract: Latent reasoning has emerged as a promising alternative to discrete Chain-of-Thought (CoT) in large language models (LLMs), enabling more expressive rea

Temporal Preference Concepts and their Functions in a Large Language Model

arXiv:2606.05194v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed to make decisions that require trading off near-term gains against long-term consequences

local-aiarxiv-cs-cl

The Tell-Tale Norm: ell_2 Magnitude as a Signal for Reasoning Dynamics in Large Language Models

arXiv:2606.06188v1 Announce Type: new Abstract: Recent work has sought to understand Large Language Models (LLMs) reasoning, yet a principled, model-intrinsic signal that captures its layer-wise reaso

Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG

model-releasesgoogle-research

Google's RAG Engine securely connects private enterprise data to LLMs to improve answer accuracy and reduce hallucinations , making it a key component of the Gemini Enterprise Agent Platform for build

USAD 2.0: Scaling Representation Distillation for Universal Audio Understanding

arXiv:2606.06444v1 Announce Type: cross Abstract: Audio encoders are critical to modern audio applications as large language models (LLMs) increasingly rely on a single encoder for diverse inputs. Whi

What Makes Two Language Models Think Alike?

arXiv:2406.12620v3 Announce Type: replace Abstract: Do architectural and training differences influence the way models represent and process language? Traditional similarity metrics tell us whether tw

A Normative Intermediate Representation for ASP-Based Compliance Reasoning

arXiv:2606.04619v1 Announce Type: new Abstract: We propose MONIR, a Modalized-Output Normative Intermediate Representation for ASP-based compliance reasoning. Its core fragment has a staged operationa

A Systematic Analysis of Linguistic Features in AI-Generated Text Detection Across Domains and Models

arXiv:2606.04177v1 Announce Type: cross Abstract: Interpretable linguistic features offer a promising approach for explaining why a given text appears machine-generated, particularly for non-expert us

And another open-weight release. Nemotron 3 Ultra has an ultra impressive capability:efficiency ratio! Design-wise, it carries forward the M…

model-releasessebastian-raschka--x

And another open-weight release. Nemotron 3 Ultra has an ultra impressive capability:efficiency ratio! Design-wise, it carries forward the Mamba-2-attention hybrid stack and LatentMoE introduced in th

ANN Search: Recall What Matters

arXiv:2606.04522v1 Announce Type: cross Abstract: Approximate nearest neighbor (ANN) search has become a core primitive in information retrieval and modern machine learning tasks, from classification

b9500

local-aillama-cpp-releases

B9500 is a release of llama.cpp that includes a Metal backend optimization reducing reset heartbeat timing from 500ms to 5ms . The release provides compiled binaries across multiple platforms includin

Can Reasoning Path still be Effective as Input? Bridging Post-Reasoning to Chain-of-Thought Compression

arXiv:2510.08647v2 Announce Type: replace-cross Abstract: Recent developments have enabled advanced reasoning in Large Language Models (LLMs) via long Chain-of-Thought (CoT), trading efficiency during

Clinical Assistant for Remote Engagement Link (CARE-link): A Web-Based Electronic Health Records Software for Managing Diabetes

arXiv:2606.04952v1 Announce Type: cross Abstract: CARE-link is an open-source, web-based clinical support platform designed to improve the management of gestational diabetes by linking clinicians and

Agents

Consensus is Strategically Insufficient: Reasoning-Trace Disagreement as a Knowledge-Representation Signal

arXiv:2606.04223v1 Announce Type: new Abstract: Multi-agent systems are commonly designed to reduce disagreement through voting, consensus protocols, debate, or fault-tolerant aggregation. We argue th

agentsarxiv-cs-ai

CRAFT: Cost-aware Refinement And Front-aware Tuning of Prompts

arXiv:2606.04661v1 Announce Type: new Abstract: Prompts tuned for accuracy often grow long, raising inference cost on every model call. The best accuracy-cost trade-off depends on the task and the bud

Culturally Grounded Personas in Large Language Models: Characterization and Alignment with Socio-Psychological Value Frameworks

arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura

safetyarxiv-cs-ai

Agents

DAR: Deontic Reasoning with Agentic Harnesses

arXiv:2606.05009v1 Announce Type: cross Abstract: Deontic reasoning is the task of answering questions by applying explicit rules and policies to case-specific facts, for example computing tax liabili

agentsarxiv-cs-ai

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

Efficient Reasoning on the Edge

arXiv:2603.16867v2 Announce Type: replace-cross Abstract: Large language models (LLMs) with chain-of-thought reasoning achieve state-of-the-art performance across complex problem-solving tasks, but th

local-aiarxiv-cs-cl

Expert-Aware Refusal Steering

arXiv:2606.04160v1 Announce Type: new Abstract: Safety alignment in instruction-tuned large language models (LLMs) depends on a model's ability to reliably refuse to respond to harmful or disallowed r

Few Tokens, Big Leverage: Preserving Safety Alignment by Constraining Safety Tokens during Fine-tuning

arXiv:2603.07445v2 Announce Type: replace Abstract: Large language models (LLMs) often require fine-tuning (FT) to perform well on downstream tasks, but FT can induce safety-alignment drift even when

FoeGlass: Simple In-Context Learning Is Enough for Red Teaming Audio Deepfake Detectors

arXiv:2606.05101v1 Announce Type: cross Abstract: Audio deepfake detection (ADD) models are critical for countering the malicious use of text-to-speech (TTS) models. Evaluating and strengthening ADD m

researcharxiv-cs-lg

GenSpan: Generation-Calibrated Motion Span Priors for Multi-Verb Video Corpus Moment Retrieval

arXiv:2603.22121v2 Announce Type: replace-cross Abstract: Video Corpus Moment Retrieval (VCMR) aims to retrieve both the correct video and its temporal segment corresponding to a natural-language quer

Geometry-Aware Hallucination Detection in Large Language Models

arXiv:2601.06196v3 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior wor

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orc…

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HT

model-releasesdair-ai--x

Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair

arXiv:2606.05030v1 Announce Type: new Abstract: Autoregressive chain-of-thought (CoT) reasoning in large language models (LLMs) is fundamentally forward-directed: each step conditions only on prior to

Applications

KITE: Kernelized and Information Theoretic Exemplars for In-Context Learning

arXiv:2509.15676v2 Announce Type: replace-cross Abstract: In-context learning (ICL) has emerged as a powerful paradigm for adapting large language models (LLMs) to new and data-scarce tasks using only

applicationsarxiv-cs-ai

Tutorials

Large Language Models Hack Rewards, and Society

arXiv:2606.04075v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, enabling large language models (LLMs) to learn from rewards. We observe that

tutorialsarxiv-cs-ai

LiSeCo: Linear Semantic Control for Language Generation

arXiv:2405.15454v4 Announce Type: replace Abstract: The prevalence of Large Language Models (LLMs) in critical applications highlights the need for controlled language generation methods that are both

MemoryDocDataSet: A Benchmark for Joint Conversational Memory and Long Document Reasoning

arXiv:2606.04442v1 Announce Type: cross Abstract: AI systems increasingly need to combine two demanding capabilities: navigating multi-session conversation history and performing deep reading comprehe

Multi-SPIN: Multi-Access Speculative Inference for Cooperative Token Generation at the Edge

arXiv:2606.04581v1 Announce Type: cross Abstract: Speculative inference (SPIN) was originally developed as an efficient architecture to accelerate Large Language Models (LLMs). In this work, we propos