Search: “models”

EDCT-Bench: Uncovering Faithfulness Gaps in VLMs via Explanation-Driven Counterfactual Testing

arXiv:2609.17953v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can produce Natural Language Explanations (NLEs) that sound plausible yet remain inconsistent with the visual evidence t

17 Sept 2026

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English Word Sense Disambiguation in 2026: When the Labels Become the Bottleneck

DGX agent

arXiv:2609.17554v1 Announce Type: new Abstract: In English all-words word sense disambiguation (WSD), the labels, not the models, have become the bottleneck: frontier LLMs are accurate enough that the

model-releasesarxiv-cs-cl

17 Sept 2026

PBEBench: A Multi-Step Programming by Examples Reasoning Benchmark inspired by Historical Linguistics

arXiv:2505.23126v5 Announce Type: replace Abstract: Although many benchmarks evaluate the reasoning abilities of Large Language Models (LLMs) within domains such as mathematics, coding, or data wrangl

17 Sept 2026

TAME: Token Attribution and Masking for Emergent misalignment

arXiv:2609.16754v1 Announce Type: cross Abstract: Fine-tuning an aligned language model on narrow, flawed data can induce harmful behavior far outside the training domain, known as emergent misalignme

16 Sept 2026

TIAO: Token Importance-Aware Policy Optimization for Text Summarization

arXiv:2609.16748v1 Announce Type: new Abstract: Text summarization requires models to condense content while preserving key qualities such as consistency and coherence. Large language models (LLMs) ha

16 Sept 2026

What Do Hallucinations Reveal About Multimodal Reasoning? Diagnosing Visual Grounding Failures via Contrastive Decoding Probes

arXiv:2609.16646v1 Announce Type: new Abstract: When strong multimodal models are widely available, progress requires new scientific methodologies beyond benchmark scores---using models as instruments

16 Sept 2026

AdaFlash: Adaptive Speculative Decoding via On-Policy Distilled Diffusion Drafters

arXiv:2607.19223v2 Announce Type: replace-cross Abstract: Speculative decoding, in which a lightweight draft model first generates a draft sequence that is then verified by the target model, has becom

safetyarxiv-cs-cl

BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents

arXiv:2609.12394v2 Announce Type: replace Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent ga

DNF-SR: Dual-Input and Negative-Aware Feature Fine-Tuning for Real-World Image Super-Resolution

arXiv:2609.15120v1 Announce Type: new Abstract: Benefiting from the powerful generative priors of diffusion models, diffusion-based real-world image super-resolution (Real-ISR) methods have demonstrat

Issue Bias in Generative AI Writing Assistance: Political Issues and LLMs in the Swedish 2026 Election

arXiv:2609.15207v1 Announce Type: new Abstract: Generative AI writing assistants and the Large Language Models (LLMs) that power them are increasingly part of how voters gather information before elec

K-Bench: A Benchmark for LLM Unlearning in Agentic Deployments

arXiv:2609.12808v2 Announce Type: replace Abstract: Unlearning benchmarks such as TOFU and MUSE certify forgetting by reading the model's final answer, where a model that refuses to answer already cou

Sweet Talkers: How Query Formulation Shapes Sycophancy in Romantic Relationship Advice

arXiv:2609.13841v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for emotional support and relationship advice, where a model's tendency to preserve a user's face can

Research

Estimating Inconsistency Response Surfaces under Uncertainty in Cyber-Physical System Development

arXiv:2609.11331v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) are commonly represented through multiple interconnected models. During development, CPS consistency requires that shared m

researcharxiv-cs-lg

11 Sept 2026

HiPerViT: A Hierarchical Perceiver-Vision Transformer Architecture for Multi-Scale Texture Recognition

arXiv:2609.10917v1 Announce Type: new Abstract: Texture recognition remains challenging for modern vision models because discriminative evidence is often carried by higher-order spatial statistics rat

11 Sept 2026

Measuring Progress in Reasoning Toward Mathematical Discovery with Automatic Verification

arXiv:2603.15617v2 Announce Type: replace Abstract: Can AI make progress on important, unsolved mathematical problems? Large language models are now capable of sophisticated mathematical and scientifi

11 Sept 2026

Agentic ML Exploration (A-MLE) for Ads Ranking

arXiv:2609.08248v1 Announce Type: new Abstract: Modern industrial ads ranking stacks are increasingly bottlenecked not by model capacity or training compute, but by the throughput of human ML iteratio

Learning with Synthetic Data via SGD in High-Dimensional Linear Regression

arXiv:2609.09572v1 Announce Type: cross Abstract: Synthetic data has become a promising way to scale model training beyond limited human-generated data but it may also induce strong model collapse (Do

safetyarxiv-cs-lg

Measuring LLM Sycophancy under Sustained Multi-Turn Pressure

arXiv:2609.09090v1 Announce Type: cross Abstract: Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations t

Pretraining and Distillation Matter More Than Architecture Family for Label-Free Single-Cell Classification

arXiv:2609.09863v1 Announce Type: new Abstract: Choosing a deep learning architecture for label-free single-cell classification remains an open question, with microscopy benchmarks reporting conflicti

SEA-SpeechBench: A Large-Scale Multitask Benchmark for Speech Understanding Across Southeast Asia

arXiv:2609.09672v1 Announce Type: new Abstract: The rapid advancement of audio and multimodal large language models has unlocked transformative speech understanding capabilities, yet evaluation framew

Semigroup-JEPA: Latent Dynamics Consistency for Zero-Shot Physics Generalization

arXiv:2609.10464v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architecture (JEPA) world models learn a compact latent representation of the world that supports prediction and planning,

Adapting Neural Robot Dynamics on the Fly for Predictive Control

model-releasesarxiv-cs-ro

arXiv:2604.04039v2 Announce Type: replace Abstract: Accurate dynamics models are critical for the design of predictive controllers for autonomous mobile robots. Physics-based models are often too simp

Ambient @ EgoProactive 2026 : Proactive Egocentric Assistance with Visually Grounded Supervision

arXiv:2609.07099v1 Announce Type: new Abstract: We present our submission to the EgoProactive track of the ECCV 2026 Wearable AI Challenge, which ranked first in the large-model division and second in

DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space

arXiv:2509.25180v3 Announce Type: replace Abstract: Existing text-to-image diffusion models excel at generating high-quality images, but face significant efficiency challenges when scaled to high reso

safetyarxiv-cs-cv

Hyperparameter Scaling Laws Across MoE Sparsity

arXiv:2609.08690v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models expand model capacity without a proportional increase in training compute, but increasing sparsity makes reliable hyperp

MOLE: Detecting Insider Threats in AI Agents

arXiv:2609.06966v1 Announce Type: new Abstract: Model misalignment, prompt injection, or operator misuse could lead AI agents operating frontier-lab accounts to exfiltrate model weights, poison traini

STSG-VQA: Evidence-Grounded Temporal Question Answering from Surgical Spatio-Temporal Scene Graphs

arXiv:2609.08543v1 Announce Type: new Abstract: Despite recent advances in surgical vision-language models (VLMs), temporal reasoning remains limited because existing supervision is largely frame-cent

Spectral characteristics of autoencoder parameters as a vector representation of data

arXiv:2609.03495v1 Announce Type: new Abstract: This paper examines the relationship between the parameters of autoencoder models and the statistical properties of the data on which they are trained.

4 Sept 2026

DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents

arXiv:2609.02059v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved strong performance on structured visual understanding tasks such as chart and document question a

3 Sept 2026

How Fast Do Agents Rot? An Empirical Study of Long-Horizon Degradation in LLM Agents for Production Decision-Making

arXiv:2609.01660v1 Announce Type: cross Abstract: Production deployments of large language model (LLM) agents remain unreliable on long, multi-step workflows even as benchmark success rates climb stea

3 Sept 2026

Untangling the Mechanisms of Misleading Context in Medical Question Answering

arXiv:2609.02754v1 Announce Type: cross Abstract: Large language models now answer medical questions with expert-level performance. However, the context these systems act on can be misleading, and mis

3 Sept 2026

Compositional Machine Design as Program Synthesis with LLMs

arXiv:2510.14980v3 Announce Type: replace Abstract: Large language models (LLMs) have shown strong abilities in writing and revising programs, yet many program-synthesis benchmarks still evaluate prog

Do General NLP Embeddings Capture Ontological Reasoning?

arXiv:2609.00177v1 Announce Type: cross Abstract: General-purpose NLP embedding models perform well on linguistic tasks, but their ability to capture symbolic ontological structure remains unclear. We

EvoFlint: An Evolutionary Atlas of Multi-Turn LLM Vulnerabilities

arXiv:2609.00487v1 Announce Type: cross Abstract: Frontier language models that refuse harmful single-turn prompts often comply when the same intent is reached gradually over many turns, making multi-

Invalidation Contracts for Cross-Episode Agent Memory

arXiv:2609.00243v1 Announce Type: new Abstract: LLM agents that cache recovery suggestions from API errors can skip re-derivation in later episodes, spending fewer tokens and fewer model calls on cons

LLM-Driven Autonomous Vehicles Inherit Human Driver Biases in Pedestrian Yielding: Results and Implications From A New Benchmark

arXiv:2609.00192v1 Announce Type: new Abstract: Public trust in Autonomous Vehicles (AVs) may depend not only on technical success but also on the fairness of their decision making. While a recent tre

Post-Training Science for Supervised Fine-Tuning

arXiv:2609.01244v1 Announce Type: cross Abstract: Every supervised fine-tuning run forces the same chain of decisions, such as learning rate, batch size, LoRA or full fine-tuning, how many epochs, whi

SOVER: Formal Certification of Optimization Reformulations via LLM-Assisted SMT Verification

arXiv:2609.00728v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown remarkable promise in translating and reformulating complex mathematical optimization problems across modeling l

AcrossWAM1.0:A Modular Latent World-Action Stack for Compact Robot Policies

arXiv:2608.29937v1 Announce Type: new Abstract: Latent world-action models avoid rendering future pixels by predicting an action-relevant visual subgoal in feature space. LaWAM established this formul

safetyarxiv-cs-ai

ACTD: Anchor-Based Cross-Tokenizer Distillation with Residual Regularization

arXiv:2608.29662v1 Announce Type: new Abstract: Knowledge distillation effectively transfers reasoning capabilities from large language models to lightweight student models. To enable knowledge transf

safetyarxiv-cs-cl

Generating Workflow DAGs from Natural Language with Non-Reasoning LLMs

arXiv:2608.30250v1 Announce Type: new Abstract: This paper addresses the problem of translating natural-language routing rules written by business administrators into executable workflow graphs for en

GeoAgent: Evaluating VLM Geolocalization Through Embodied Navigation

arXiv:2608.29483v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) perform well above the human baseline in image geolocalization, a task critically important in disaster response,

Learning to Follow In-Context Watermark Instructions via Self-Distillation

arXiv:2608.29030v1 Announce Type: new Abstract: In-context watermarking (ICW) prepends an instruction to a query asking the model to embed a statistically detectable signal in its response. It thus eq

Measurement Validity in LLM Cultural Alignment

arXiv:2608.29266v1 Announce Type: cross Abstract: Researchers increasingly treat LLM survey responses as a proxy for human cultural values. This includes projecting model outputs onto instruments like

safetyarxiv-cs-ai

MedSegBenchmarker: A Raw-Count-First Framework for Controlled 2D Medical Image Segmentation Benchmarks

arXiv:2608.29677v1 Announce Type: cross Abstract: Despite rapid advances in MIS, fair and reproducible comparisons of segmentation models remain challenging due to heterogeneous datasets, inconsistent

Real-Time Deadlines Reveal Fragile Temporal Adaptation in LLM Strategic Dialogues

arXiv:2601.13206v2 Announce Type: replace Abstract: Large Language Models (LLMs) generate text token-by-token in discrete time, yet real-world communication, from therapy sessions to business negotiat

Agents

SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks

arXiv:2606.15872v2 Announce Type: replace Abstract: Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of

agentsarxiv-cs-cl

Self-Specialized Teachers for Domain Post-Training

arXiv:2608.28647v1 Announce Type: new Abstract: Target-only post-training can improve performance in a specialized domain while degrading behaviors that a general-purpose base model acquired before ad