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Modeling and Optimizing User Preferences in AI Copilots: A Comprehensive Survey and Taxonomy

arXiv:2505.21907v3 Announce Type: replace Abstract: AI copilots represent a new generation of AI-powered systems designed to assist users, particularly knowledge workers and developers, in complex, co

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Multimodal Language Models as Text-to-Image Model Evaluators

DGX agent

arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat

model-releasesarxiv-cs-ai

3 Sept 2026

NeoMME: A Single-Tower Multimodal-Native Multilingual Foundation Encoder for Efficient Fine-Tuning and Inference

arXiv:2609.01657v1 Announce Type: cross Abstract: Multimodal models often build on architectures designed for generative vision-language modeling, typically combining separately pretrained vision enco

OutageDiT: A Generative Foundation Model for Power Outage Forecasting and Scenario Simulation

arXiv:2609.01896v1 Announce Type: cross Abstract: Power-outage planning requires scenarios before an event occurs. These scenarios must represent uncertainty in magnitude, timing, and duration while p

Predictors of Loneliness in Older Adults Using Multimodal Analysis of Speech and Language

arXiv:2609.02606v1 Announce Type: new Abstract: Loneliness is a critical public health issue among older adults, linked to higher risks of depression, cognitive decline, and mortality. Scalable, objec

ProbeMatchDTI: Probe-Driven Multi-Scale Biochemical Pattern Matching for Drug-Target Interaction Prediction

arXiv:2609.02549v1 Announce Type: cross Abstract: Drug-target interaction (DTI) prediction is an important task in AI-driven drug discovery. Although recent biochemical representation learning methods

Reinforcement learning to choose optimizers

arXiv:2609.01811v1 Announce Type: cross Abstract: No single optimization method is uniformly best for all problems, and the most suitable optimizer choice can change during a run. Existing approaches

safetyarxiv-cs-lg

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

arXiv:2609.02749v1 Announce Type: new Abstract: Autonomous agents are beginning to carry out machine-learning (ML) research end to end. These agents combine a model backbone with a harness for plannin

RINSE: Robust Target-Time Normality Estimation for Zero-Shot Graph Anomaly Detection

arXiv:2609.02497v1 Announce Type: cross Abstract: Zero-shot graph anomaly detection seeks to deploy a detector trained on source graphs to unseen, unlabeled targets, yet domain shift can make source-d

applicationsarxiv-cs-ai

RVSD: Retrieval Vision Sparse Decoding for Mitigating Visual Hallucinations in Large Vision-Language Models

arXiv:2609.02731v1 Announce Type: cross Abstract: Large vision-language models have achieved remarkable success in vision-language tasks. However, they remain prone to Visual Hallucinations (VHs), und

applicationsarxiv-cs-ai

SCX Router: Streaming Zero-Shot Model Selection with a Decoder-KV Classifier and a Real-World Task Ontology

arXiv:2609.02292v1 Announce Type: new Abstract: The rapid proliferation of large language models (LLMs) and the growing diversity of their applications presents a unique optimization opportunity: sele

SelfMOTR: Revisiting MOTR with Self-Generating Detection Priors

arXiv:2511.20279v3 Announce Type: replace Abstract: End-to-end transformer architectures have driven significant progress in multi-object tracking by unifying detection and association into a single,

researcharxiv-cs-cv

Shiva-DiT: Residual-Based Differentiable Top-k Selection for Efficient Diffusion Transformers

arXiv:2602.05605v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) are costly at high resolution because self-attention scales quadratically with token sequence length. Existing p

safetyarxiv-cs-ai

Sparse Readout Prism: Explaining Logit-Lens Scores in Features Instead of Tokens

arXiv:2609.01936v1 Announce Type: cross Abstract: A language model's prediction of its next token develops across layers, and lens methods track this process by decoding intermediate hidden states int

TalkFa: A Unified Benchmark for Farsi Dialogue Generation and Understanding

arXiv:2609.01810v1 Announce Type: new Abstract: Farsi, spoken by more than 120 million people, lacks a comprehensive benchmark for dialogue generation and understanding. We introduce TALKFA, a unified

Task-Level Natural Language Priors as Learning Signals for Low-Resource LLM Training

arXiv:2609.02244v1 Announce Type: new Abstract: Large language models (LLMs) often struggle when low-resource training data are ambiguous or incomplete. Task-level natural-language priors can provide

text2ql: Multi-Target Natural Language Querying via a Language-Agnostic Intermediate Representation

arXiv:2609.02115v1 Announce Type: cross Abstract: Natural language interfaces to databases have traditionally suffered from three structural limitations: exclusive targeting of relational SQL, uncondi

The Dynamics of Continuous Mixture Collapse in Language Models

arXiv:2609.02049v1 Announce Type: cross Abstract: LLMs latent-state reasoning methods replace discrete intermediate tokens with continuous states, such as weighted mixtures of token embeddings, to ret

Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: A Comparative Study

arXiv:2507.08468v2 Announce Type: replace Abstract: This paper provides an experimental evaluation of the capability of large language models (LLMs) to assist in legal decision-making within the frame

applicationsarxiv-cs-cl

When Literature Data Mislead Artificial Intelligence in Materials Discovery

arXiv:2609.01621v1 Announce Type: cross Abstract: Artificial intelligence (AI) increasingly treats scientific literature as a data source for building databases, training predictive models, and guidin

researcharxiv-cs-lg

XMerge: Cross-Axis Selection and Reconstructive Layer Merging for LLM Depth Compression

arXiv:2609.02083v1 Announce Type: cross Abstract: Removing complete transformer layers preserves a standard serving architecture, but existing depth-compression methods can lose substantial quality, a

A Dataset for Modeling Iterative Problem-Solving

arXiv:2609.00940v1 Announce Type: new Abstract: Solving problems through repeated attempts is a sequential modeling task: at each step, the solver receives feedback and decides how to revise their sol

Local Ai

A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss

arXiv:2609.00591v1 Announce Type: new Abstract: An image may be worth a thousand words, but most captioning models describe it in only a few. Modern vision-language models produce fluent high-level ca

local-aiarxiv-cs-cv

A Mathematical Framework for Legacy, Governance, and Decision Integrity in Enterprise AI

arXiv:2609.00572v1 Announce Type: cross Abstract: Enterprise artificial intelligence is increasingly embedded in decisions that must remain lawful, explainable, adaptable, and accountable despite pers

applicationsarxiv-cs-ai

Accelerating Reinforcement Learning via MPC Solver-Gradient Guidance for Weights-varying MPC

arXiv:2609.01061v1 Announce Type: cross Abstract: In Model Predictive Control (MPC), cost-function weights shape closed-loop behavior, yet changing conditions often make fixed parametrizations subopti

safetyarxiv-cs-lg

AgentProv: Auditing Agentic LLM API Providers via Tool-use Policy Probes

arXiv:2609.00052v1 Announce Type: cross Abstract: Commercial LLM APIs advertise a specific foundation model, but the served backbone may be silently substituted, quantized, or wrapped, for example to

Authority Bias in Conversational Search Engines for Academic Paper Recommendation

arXiv:2609.00248v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as conversational search engines for academic literature, yet whether they judge papers on content or

safetyarxiv-cs-ai

Beyond Tokens: Semantic-Aware Speculative Decoding for Efficient Inference by Probing Internal States

arXiv:2602.03708v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve strong performance across many tasks but suffer from high inference latency due to autoregressive decoding. The

CameraEditor: Camera-Controlled Image Editing via Video-Prior Sequential Modeling

model-releasesarxiv-cs-cv

arXiv:2609.01479v1 Announce Type: new Abstract: Beyond semantic content, camera parameters play a pivotal role in dictating the geometric perspective and appearance of any given image. While recent im

Can LLMs Discover Scientific Laws in Real and Parallel Worlds?

arXiv:2609.01552v1 Announce Type: new Abstract: Scientific equation discovery has long been central to scientific progress, proceeding through iterative cycles of hypothesis generation, observational

Agents

Creative Generation via Multi-Agent Debate: Does Debate Suppress Diversity?

arXiv:2609.00683v1 Announce Type: new Abstract: Creative generation tasks, such as narrative writing and scientific ideation, demand both high-quality outputs and distinct responses across independent

agentsarxiv-cs-cl

CWoMP: Morpheme Representation Learning for Interlinear Glossing

arXiv:2603.18184v2 Announce Type: replace Abstract: Interlinear glossed text (IGT) is a standard notation for language documentation which is linguistically rich but laborious to produce manually. Rec

DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems

arXiv:2601.06853v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) prompting is widely adopted for mathematical problem solving, including in low-resource languages, yet its behavior under irr

Do LLMs Know Your Neighborhood? Auditing LLM Priors for Neighborhood-Level Mobility Prediction and Structural Alignment

arXiv:2609.00345v1 Announce Type: new Abstract: Human mobility is central to urban planning, transportation, public health, and emergency response, yet fine-grained trajectory data are often proprieta

safetyarxiv-cs-lg

DSG: Dynamic 3D Scene Graph Construction for Embodied Agents in Changing Indoor Environments

model-releasesarxiv-cs-ro

arXiv:2609.00619v1 Announce Type: new Abstract: In indoor environments, object positions frequently change due to human activities or embodied-agent interactions, causing previously constructed scene

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

arXiv:2609.01603v1 Announce Type: cross Abstract: Evaluating software engineering agents on realistic benchmarks is costly, since each task may require multi-step code exploration, modification, and t

EGT-KG: Evidence-Grounded Typed KG Retrieval for Practical Scientific QA with Small Language Models

arXiv:2609.00479v1 Announce Type: new Abstract: For emerging scientific research domains, local Small Language Models (SLMs) are becoming more attractive, as they offer stronger privacy control and mo

Evaluating Style-Personalized Text Generation: Challenges and Directions

arXiv:2508.06374v4 Announce Type: replace Abstract: With the surge of large language models (LLMs) and their ability to produce customized output, style-personalized text generation--'write like me'--

FloydNet: A Learning Paradigm for Global Relational Reasoning

arXiv:2601.19094v3 Announce Type: replace-cross Abstract: Learning algorithmic computation often requires explicit relational intermediate states, yet many graph processors maintain their primary stat

Generative artificial intelligence for reliable mechanistic reasoning for corrosion

model-releasesarxiv-cs-lg

arXiv:2609.00099v1 Announce Type: new Abstract: Corrosion accounts for approximately 4% of global GDP, and reliable prediction is essential for timely mitigation. Machine learning effectively predicts

Generativism: Toward a Learning Theory for the Age of Generative Artificial Intelligence

arXiv:2606.12441v2 Announce Type: replace-cross Abstract: The four dominant learning theories of behaviorism, cognitivism, constructivism, and connectivism show significant conceptual limitations as g

Good Memory Has ECC: Evaluating the Memory of Vision-Language Models Beyond Accuracy

arXiv:2609.00103v1 Announce Type: cross Abstract: Memory is widely viewed as an important unsolved problem for LLMs and VLMs, and current benchmarks typically evaluate it by testing accuracy over long

HiMPO: Hindsight-Informed Memory Policy Optimization for Less-Entangled Credit in Long-Horizon Agents

arXiv:2606.16285v2 Announce Type: replace Abstract: Long-horizon agents rely on memory mechanisms to compress interaction history, but optimizing memory writing faces a distinct credit assignment chal

safetyarxiv-cs-cl

Hints Help But Do They Teach? Evaluating Skills Transfer in Code Generation

arXiv:2609.01106v1 Announce Type: cross Abstract: When a hint turns a failing generated program into a passing one, does it provide missing information or merely steer the model toward a solution it c

How Correct Is Your Answer? A Semantic Correctness Framework for Open QA Evaluation

arXiv:2609.01369v1 Announce Type: new Abstract: Reliable evaluation of open-ended question answering remains a bottleneck for measuring answer correctness of modern LLMs. Unlike multiple-choice tasks,

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

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

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

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