Search: “context”

Multi-Expert Conformal Risk Control for Pairwise LLM Judging in Open-Ended Dialogue

arXiv:2608.26529v1 Announce Type: new Abstract: In this paper, we explore multi-expert Conformal Risk Control (CRC) algorithms for pairwise LLM-as-a-Judge evaluation in open-ended dialogue. Our core i

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Research

Multi-Person Human Motion Forecasting in Complex Scenes

DGX agent

arXiv:2608.27039v1 Announce Type: cross Abstract: Accurately forecasting the movement of people in complex scenes requires reasoning over the past and present state of the entire environment. In this

researcharxiv-cs-ai

28 Aug 2026

Multi2AV-Safety: Benchmarking Safety in Multimodal-to-Audio-Video Generation

arXiv:2608.26535v1 Announce Type: new Abstract: Audio-video generation is rapidly moving from prompt-driven synthesis toward multimodal conditioning, where text, images, audio, and video can jointly s

NeuronFuzz: Safety Neuron Guided Fuzzing for LLM Safety Evaluation

arXiv:2608.26222v1 Announce Type: cross Abstract: Safety evaluation is critical for assessing whether aligned Large Language Models (LLMs) remain robust against jailbreak attacks. Existing automated t

Omni-Interactive Universal Embedder

arXiv:2608.27044v1 Announce Type: new Abstract: Multimodal representation learning has been shifting from traditional two-tower architectures to large language model (LLM)-based embedders due to their

Performance Foundations of Parallel & Distributed Reasoning Language Models

arXiv:2608.27046v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) and other RL-style post-training paradigms have been used for aligning large language models (LL

PILOT in the Loop: Live Self-Improvement for Long-Horizon Agents

arXiv:2608.26530v1 Announce Type: new Abstract: Long-horizon agent runs generate experience that can improve both the current run and future work. Most self-improvement methods process this experience

PragAlign: Evidence-Sensitive Reply Assistance Across Chinese and Japanese Appropriateness Judgments

arXiv:2608.26700v1 Announce Type: new Abstract: Reply assistance in multilingual settings requires linguistic competence and culturally situated judgments of appropriateness. We present PragAlign, whi

Predicting Quantifiability from Primary Screens to Prioritize Dose-Response Profiling

arXiv:2608.26538v1 Announce Type: new Abstract: High-throughput drug screening relies on low-cost primary assays to prioritize compounds for more expensive dose-response profiling, where potency is ul

researcharxiv-cs-lg

pro-team at LLMs4OL 2026 Tasks Flagship and Reuse: Retrieval-Augmented Generation and Vocabulary-Constrained Filtering for Ontology Learning

arXiv:2608.27101v1 Announce Type: new Abstract: Ontology learning from text remains challenging despite significant progress in Large Language Models (LLMs), which can hallucinate domain terms, produc

RCMN: Understanding Misleadingness in Influential Public Discourse

arXiv:2608.27358v1 Announce Type: cross Abstract: Influential public discourse shapes public beliefs and can also mislead, not only through what is stated, but also through how information is framed,

RedEvoAgent: Automatic Red-Teaming Agent with Experience-Driven Skill Evolution

arXiv:2608.27439v1 Announce Type: cross Abstract: LLM-based agents are increasingly deployed in product-level execution harnesses, where jailbreaks can trigger harmful tool use and persistent state ch

ReViCo: Unveiling the Limitations of VLMs in Visual Text Understanding via Error Correction

model-releasesarxiv-cs-cv

arXiv:2608.27154v1 Announce Type: new Abstract: Vision Language Models (VLMs) have shown great success in general visual tasks, yet they still struggle to deeply understand text within images. In this

SKILL.state: Scalable Long-Horizon Agent Skills

arXiv:2608.26263v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly act as autonomous agents executing complex, long-running procedural skills. Existing agent runtimes maintain e

SPT: Skills as Pre-Training Data for Agentic Language Models

arXiv:2608.26563v1 Announce Type: new Abstract: Agentic (tool-using) language models are mainly trained on tool-call traces and agent trajectories during post-training. These data provide direct behav

agentsarxiv-cs-cl

STAR : Sentence Translation Alignment Rate for Document-to-Document Machine Translation

arXiv:2608.27161v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled a shift from sentence-level to document-to-document (Doc2Doc) machine translation, promising improved global c

safetyarxiv-cs-cl

STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

arXiv:2608.27225v1 Announce Type: cross Abstract: Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing work

SWE-Prime: Fewer Trajectories, Better Performance

arXiv:2608.27449v1 Announce Type: cross Abstract: To improve large language models' ability to resolve real-world software issues, prior work has focused on constructing large-scale agent trajectory d

TabuLM: Morphology-Aware Tabular Pre-training for Low-Resource Languages

arXiv:2608.26923v1 Announce Type: new Abstract: We present TabuLM, the first language model pre-trained on Kinyarwanda tabular data. Kinyarwanda is a morphologically rich Bantu language spoken by over

TEMPLAR Wales: A georeferenced environmental and toponymic dataset of Welsh settlements

arXiv:2608.26970v1 Announce Type: cross Abstract: Place names provide persistent records of how landscapes have been described and organised, but their quantitative reuse requires explicit separation

Tutorials

The BS-meter: Detecting Politics and Labour through ChatGPT's Language

arXiv:2411.15129v3 Announce Type: replace-cross Abstract: What can we learn about language from studying how it is used by ChatGPT and other large language model (LLM)-based chatbots? In this paper, w

tutorialsarxiv-cs-ai

The Latent Diagnostic Taxonomy: A Framework for Constructing Classifiers and Diagnosing Their Decisions, Applied to Prompt Injection Detection

arXiv:2608.26423v1 Announce Type: cross Abstract: This paper proposes a framework for constructing a classifier as a safeguard layer, and for developing a complementary diagnostic that identifies whic

TraceBench: Controlled Evaluation of LLM Agents for Time-Series Root-Cause Attribution

model-releasesarxiv-cs-lg

arXiv:2608.27182v1 Announce Type: new Abstract: LLM agents are increasingly applied to anomaly detection and root-cause analysis in time-series observations collected from real-world systems; however,

Training-Time Explainability for Multilingual Hate Speech Detection: Aligning Model Reasoning with Human Rationales

arXiv:2608.26125v1 Announce Type: cross Abstract: Online hate against Muslim communities often appears in culturally coded, multilingual forms that evade conventional AI moderation. Such systems, thou

Using Poly-Encoders for Computationally Efficient Automated Creativity Assessment

arXiv:2608.26165v1 Announce Type: cross Abstract: Automated creativity assessment has been a long standing challenge, with traditional methods often being resource intensive or lacking practical accur

Vagdhenu: A Vrutta (Meter) Aware Shloka-to-Chant (TTS) System for Sanskrit

arXiv:2608.26146v1 Announce Type: new Abstract: We present Vagdhenu, a vrutta (meter) aware shloka-to-chant system for Sanskrit: a text-to-speech system that maps a metrical verse to its chanted paray

Video-OPSD: Exploiting Privileged Visual Evidence for On-Policy Self-Distillation in Video Large Language Models

arXiv:2608.27065v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has recently emerged as an effective post-training paradigm that improves policy optimization through dense token-lev

safetyarxiv-cs-cv

Visual Information-Guided Parallel Decoding for Diffusion Multimodal Large Language Models

arXiv:2608.26580v1 Announce Type: cross Abstract: Diffusion multimodal large language models (dMLLMs) have recently emerged as a new decoding paradigm for multimodal generation. Starting from a fully

WALL-SS: Scaling Long-horizon World Models via Next-Scale Autoregression

arXiv:2608.26239v1 Announce Type: new Abstract: Generative world models provide robots with predictive models of how the world evolves under interaction, with growing potential for simulation, plannin

safetyarxiv-cs-ro

When Memory Takes Gradients: Collaborative Vector Memory for Agentic Recommender Systems

arXiv:2608.26895v1 Announce Type: cross Abstract: Agentic recommender systems ground each decision of a large language model (LLM) in a persistent memory of the user, and in existing agents that memor

When Tool Outputs Become Commands: Separating Action Induction from Runtime Authorization in Tool-Augmented LLM Agents

arXiv:2608.27146v1 Announce Type: new Abstract: Tool-augmented LLM agents must rely on untrusted runtime Observations to complete open-ended tasks; however, when tool outputs no longer merely provide

Which India Survives Translation? Narrative Homogenisation Across Indian Oral Traditions in LLMs

arXiv:2608.26123v1 Announce Type: new Abstract: Large language models (LLMs) are trained predominantly on English-language internet text that over-represents certain cultural narratives, raising conce

Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI

arXiv:2608.26182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for verbal interaction in social robots, yet prompt design in human-robot interaction (HRI) remains u

Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performance

arXiv:2608.26480v1 Announce Type: cross Abstract: Multi-agent large language model systems are widely reported to beat single-model baselines, but the evidence is mixed, and comparisons are usually co

Applications

A Dual-Transformer for Multi-Camera View Recommendation

arXiv:2608.25601v1 Announce Type: new Abstract: Multi-camera systems are foundational to modern media production, and multi-camera editing is a critical task. This involves the proper selection of the

applicationsarxiv-cs-cv

A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots

arXiv:2606.19660v2 Announce Type: replace-cross Abstract: Prompt injection is ranked as the most critical vulnerability in large language model (LLM) deployments by the OWASP Top 10 for LLM Applicatio

Local Ai

A Lightweight Multimodal Vision-Language Framework for Early-Stage Anatomical Green Fruit Classification in Commercial Orchards

arXiv:2608.24935v1 Announce Type: new Abstract: Accurate identification of early-stage apple fruitlet anatomical structures, including the calyx, fruitlet body, and peduncle, is essential for robotic

local-aiarxiv-cs-cv

Adaptive Triggering for Bias Correction in LLM Reasoning

arXiv:2608.25379v1 Announce Type: new Abstract: Chain-of-thought prompting can expose and amplify demographic stereotypes within an LLM's intermediate reasoning and create a failure mode that final-an

safetyarxiv-cs-cl

Advantage-Driven Explicit Memory for Social Navigation

arXiv:2608.25610v1 Announce Type: new Abstract: Robot policies are predominantly learned with classical parametric variants of imitation learning or RL, where training stores the agent's behavior excl

safetyarxiv-cs-ro

Applications

Are LLM-Enhanced GNNs Privacy-Safe?

arXiv:2608.25727v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced graph neural networks (GNNs) by enriching node representations with semantic information, giving ris

applicationsarxiv-cs-lg

AWM: Answerable Working Memory for Long-Document VQA Agents

arXiv:2608.25618v1 Announce Type: new Abstract: Long-document visual question answering increasingly relies on VLM agents that retrieve candidate pages, inspect page images, write findings to working

agentsarxiv-cs-cl

Boosting Reasoning in Large Multimodal Models via Activation Replay

arXiv:2511.19972v4 Announce Type: replace Abstract: Recently, Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as an effective approach to incentivizing reasoning capability in Large

safetyarxiv-cs-cv

BRIDLE: Generalized Self-supervised Learning with Quantization

arXiv:2502.02118v2 Announce Type: replace-cross Abstract: Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, redu

researcharxiv-cs-cv

CEDAR: Controlled and Event-Driven Demand Forecasting via Residual Decomposition

arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future

safetyarxiv-cs-lg

DCEO: Direct Causal Effect Optimization for Long-Term User Value Modeling in E-commerce Search

arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand

safetyarxiv-cs-lg

DCGC: Draft-Conditioned Global Correction for Complex Reasoning with Masked Diffusion Models

arXiv:2608.25428v1 Announce Type: new Abstract: Correcting flawed reasoning traces remains a significant challenge for Large Language Models (LLMs), whose autoregressive generation can propagate early

EduAgentQG: Multi-Agent Personalized Mathematics Question Generation with Explicit Diversity and Objective-Aware Evaluation

arXiv:2511.11635v2 Announce Type: replace-cross Abstract: In intelligent education, personalized mathematics question generation aims to produce mathematics questions that satisfy educational requirem

Applications

EduDial: Constructing a Large-scale Multi-turn Teacher-Student Dialogue Corpus

arXiv:2510.12899v3 Announce Type: replace Abstract: Recently, several multi-turn dialogue benchmarks have been proposed to evaluate the conversational abilities of large language models (LLMs). As LLM

applicationsarxiv-cs-cl