Search: “models”

SUP-MIMIC: A Multi-Task Clinical Diagnosis Benchmark for Evaluating LLMs' Robustness to Contradictory Evidence

arXiv:2608.29582v1 Announce Type: cross Abstract: Current evaluations of large language models (LLMs) primarily focus on factual knowledge retrieval, overlooking the fundamental challenge of navigatin

1 Sept 2026

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Safety

The Safety Relay in Roleplay Jailbreaks: A Component-Resolved Causal Analysis of Harm Recognition and Refusal

DGX agent

arXiv:2608.30585v1 Announce Type: new Abstract: Large language models are trained to follow instructions while refusing harmful requests. Jailbreaks exploit this balance to elicit content a model woul

safetyarxiv-cs-lg

1 Sept 2026

Where Induction Runs Out: Description-Length Difficulty and the Memorisation Gap in Integer-Sequence Benchmarks

arXiv:2608.29411v1 Announce Type: new Abstract: Integer sequences from the On-Line Encyclopedia of Integer Sequences (OEIS) are increasingly used to benchmark mathematical reasoning in language models

1 Sept 2026

Characterization of Request and Token Energy Costs for LLM Inference Workloads on GPU Platforms

arXiv:2608.28044v1 Announce Type: cross Abstract: Large language model (LLM) inference serving is priced by tokens, but GPU energy is consumed over inference windows. This accounting mismatch makes to

31 Aug 2026

Memorization Is Not Extraction: Tight Differential-Privacy Bounds and Audit Blind Spots

arXiv:2608.27782v1 Announce Type: cross Abstract: Memorization in large language models is measured through a zoo of definitions whose formal relations are unknown, and differential privacy (DP) is tr

31 Aug 2026

Speculative Probing: LLM Monitoring at Speculative-Decoding Cost

arXiv:2608.28099v1 Announce Type: cross Abstract: Real-time classification during language model inference is valuable for safety filtering, behavioral analysis, and model monitoring, but current appr

31 Aug 2026

4DSynth: Controllable Procedural World Synthesis for Dynamic Embodied Simulation

arXiv:2608.26947v1 Announce Type: cross Abstract: Embodied agents need environments that are visually diverse, physically interactive, and changing over time. Procedural simulators can generate large

DeflectBench: A Benchmark for Evaluating Rhetorical Fallacy Generation in LLMs

arXiv:2608.26119v1 Announce Type: new Abstract: Whether large language models can be prompted to generate rhetorical fallacies on demand, and whether current safety post-training constrains this behav

Agents

Diff Mining: Logit Differences Reveal Finetuning Objectives

arXiv:2608.26462v1 Announce Type: cross Abstract: Finetuning has become the gold standard for refining existing behaviors and inducing new ones in language models, yet it often remains unclear exactly

agentsarxiv-cs-ai

Evaluating Confidence-Gated Retrieval with Matched Trajectory Replay

arXiv:2608.26846v1 Announce Type: cross Abstract: Interactive language-model agents use confidence signals to decide whether to answer immediately, retrieve additional evidence (from memory or externa

GRAIN: Bridging Name and Narrative Shifts in Real-World Graph Reasoning through Invariance-Rewarded Agentic RL

arXiv:2608.27142v1 Announce Type: new Abstract: Despite their potential in standardized graph tasks, Large Language Models (LLMs) remain brittle to real-world shifts in node identifiers and task formu

Syntax vs. Semantics: How Transformers Learn Deep Dependencies

arXiv:2608.26139v1 Announce Type: cross Abstract: Large Language Models demonstrate remarkable syntactic fluency, yet the optimization dynamics governing their acquisition of deep semantic dependencie

Think3D: Thinking with Space for Spatial Reasoning

arXiv:2601.13029v4 Announce Type: replace Abstract: While Vision-Language Models (VLMs) excel at 2D visual understanding, they remain constrained by 2D-centric paradigm that severely limits genuine 3D

WikiSkill: Compiling Agent Experience into Persistent Knowledge for Skill Evolution

arXiv:2608.27454v1 Announce Type: new Abstract: Agent skills package specialized knowledge and workflows into reusable resources that extend AI agent capabilities. Recent work automatically discovers

EXAONE Tabular 1.0 : Technical Report

arXiv:2608.25774v1 Announce Type: new Abstract: EXAONE Tabular is a compact tabular foundation model family for classification and regression via in-context learning, producing predictions without dat

Research

iFlip: Iterative Feedback-driven Counterfactual Example Refinement

arXiv:2601.01446v2 Announce Type: replace Abstract: Counterfactual examples are minimal edits to an input that alter a model's prediction. They are widely employed in explainable AI to probe model beh

researcharxiv-cs-cl

NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates

arXiv:2608.25080v1 Announce Type: new Abstract: Time series forecasting models are widely used in high-stakes settings, yet their predictions remain difficult to interpret because existing post-hoc me

RA-VLA: Retrieval-Augmented VLA for Test-Time Adaptation

model-releasesarxiv-cs-ro

arXiv:2608.25585v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a versatile foundation for general robotic manipulation, yet they exhibit significant brittleness when confr

Towards Fine-Grained Text-to-3D Quality Assessment: A Benchmark and A Two-Stage Rank-Learning Metric

arXiv:2509.23841v3 Announce Type: replace Abstract: Recent advances in Text-to-3D (T23D) generative models have enabled the synthesis of diverse, high-fidelity 3D assets from textual prompts. However,

EXAM^2: nderline{Ex}tending nderline{A}udio Understanding in nderline{M}ultilingual and nderline{M}ultimodal Analysis

arXiv:2608.23758v1 Announce Type: cross Abstract: Recent large audio language models (LALMs) have achieved impressive progress in audio understanding. However, existing evaluations remain largely cons

OmniJudge or OmniBias? Diagnosing Multimodal Judges through Balanced, Decoupled Lenses

arXiv:2608.24160v1 Announce Type: new Abstract: Multimodal understanding models that can jointly judge text-to-image (T2I), text-to-video (T2V) and text-to-speech (TTS) generation are increasingly use

Parameter-Efficient Self-Supervised Adaptation for EEG-FM under Fixed Computational Budgets

arXiv:2608.24727v1 Announce Type: cross Abstract: EEG foundation models pretrained via self-supervised learning promise transferable representations, but their generalization remains limited, especial

RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation

arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem

Hardware

Serving Masked Diffusion LLMs: Characterization and Design Principles from Real Hardware

arXiv:2608.23807v1 Announce Type: new Abstract: Masked diffusion language models (dLLMs) can in principle generate text faster than autoregressive (AR) models, since they denoise many tokens at once.

hardwarearxiv-cs-ai

Research

Steering Recurrent Reasoners at Inference Time with Readout Feedback

arXiv:2608.24136v1 Announce Type: new Abstract: Recurrent models, which repeatedly update latent states with shared computation blocks, have emerged as powerful architectures for solving complex reaso

researcharxiv-cs-lg

The Handoff Tax: Continuing Non-Native Trajectories in LLM Agents

arXiv:2608.24358v1 Announce Type: new Abstract: Coding agents perform long-running tasks spanning dozens of model calls, tool uses, and code edits. As these runs unfold, users face a practical cost-qu

Research

The Loss Floor of Denoising Score Matching: Fisher Geometry from Schrodinger Bridges

arXiv:2608.23916v1 Announce Type: new Abstract: Denoising score matching trains diffusion models by regressing onto a conditional score, although generation ultimately requires the marginal score. The

researcharxiv-cs-lg

When Can One Neuron Fix Repetition Loops in LLMs?

arXiv:2606.13705v2 Announce Type: replace-cross Abstract: The Gemma 4 instruction-tuned models share a reproducible failure: on long factual enumeration prompts, such as TV episodes, the 88 IAU conste

Safety

Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs

arXiv:2608.22854v1 Announce Type: new Abstract: Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style mod

safetyarxiv-cs-lg

25 Aug 2026

Vibe Coding on Trial: Operating Characteristics of Unanimous LLM Juries

arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the

25 Aug 2026

Annotations as Rollouts: Efficient and Scalable Reinforcement Learning for Video MLLMs

arXiv:2608.20492v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have become a prevailing paradigm for unified video perception. However, post-training on large multi-task data

Asymmetric Capacity Allocation in Self-Refinement Pipelines

arXiv:2608.21345v1 Announce Type: new Abstract: Self-refinement, typically structured as generation, critique, and revision, is a widely adopted paradigm for improving LLM generation and serves as a c

Llama-Mobile: Efficient 2.7-Bit Quantization of VLMs

arXiv:2608.21134v1 Announce Type: new Abstract: Deploying vision-language models (VLMs) on mobile devices is challenging due to their significant memory and compute requirements. We present a framewor

When Do LLMs Replace Fine-Tuned NLU? A Decision Framework for Intent Detection in Production Conversational Systems

arXiv:2608.20371v1 Announce Type: cross Abstract: A common claim is that zero-shot large language models (LLMs) can replace fine-tuned NLU classifiers for intent detection. We test this claim head-to-

Local Ai

Auditing Recorded Predictive Lead Service-Line Classifications Against Physical Verification: A Statewide Study of New York

arXiv:2608.19922v1 Announce Type: new Abstract: Under the US Lead and Copper Rule Revisions, a utility may determine a service line's material with a predictive model instead of inspecting it. New Yor

local-aiarxiv-cs-lg

21 Aug 2026

Learning-Based Speed Estimation from Accelerometer-Only Inertial Sensing

arXiv:2401.07468v4 Announce Type: replace-cross Abstract: The proposed model, CarSpeedNet, estimates scalar vehicle speed from a window of three-axis smartphone acceleration, without gyroscope, wheel-

21 Aug 2026

CamWorldQA: Perceptual Quality Assessment of Camera-Controlled World Video Generation

arXiv:2608.18710v1 Announce Type: new Abstract: Recent advances in generative video models have enabled camera-controlled world video generation, allowing models to synthesize videos under user-define

20 Aug 2026

Safety

To Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization

arXiv:2608.18770v1 Announce Type: cross Abstract: Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fa

safetyarxiv-cs-ro

20 Aug 2026

Abra: Scaling Diffusion Image Training

arXiv:2608.17286v1 Announce Type: new Abstract: Compute-optimal scaling laws guide the training of frontier language models yet remain largely unexplored for visual generation. We present a systematic

19 Aug 2026

Applications

Evaluating and improving crop-yield forecasting methods during extreme drought

arXiv:2608.17971v1 Announce Type: new Abstract: The impact of climate variability on food production has led to the creation of various forecasting models that uses machine learning (ML), numerical we

applicationsarxiv-cs-lg

19 Aug 2026

OOD Detection for EEG-based Machine Learning in High-Risk Environments

arXiv:2608.17620v1 Announce Type: new Abstract: Machine learning models for electroencephalography (EEG) analysis show great promise across a wide range of applications, but their deployment in high-r

19 Aug 2026

Breaking the Compression Barrier: Cross-Architecture Compression Boundary Learning via Reverse Regrowth

arXiv:2608.16010v1 Announce Type: cross Abstract: Model compression is critical for deploying networks on resource-constrained edge devices. While pruning-based methods can significantly reduce model

HLE-Verified: A Systematic Verification and Structured Revision of Humanity's Last Exam

arXiv:2602.13964v4 Announce Type: replace Abstract: Humanity's Last Exam (HLE) has become a widely used benchmark for evaluating frontier large language models on challenging, multi-domain questions.

OTel: Building Domain-Specialized Telecom LLM Foundations for Intelligent Networks

arXiv:2608.15436v1 Announce Type: new Abstract: Frontier AI models have advanced rapidly, but they still struggle with telecom-specific tasks. We present Open Telco (OTel), an open telecom AI resource

Reconstruction: A Blind Benchmark for Recovering Research Ideas from Pre-Publication Bibliographies

arXiv:2608.16645v1 Announce Type: new Abstract: Can a language model recover the true research idea of a published paper when given only that paper's pre-publication bibliography? We introduce Reconst

TAHB: A Comprehensive Benchmark for Text-Attributed Hypergraph Learning

arXiv:2608.15055v1 Announce Type: new Abstract: Hypergraphs effectively model higher-order groupwise relationships beyond pairwise interactions, while pretrained language models (PLMs) and large langu

VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding

arXiv:2608.14718v1 Announce Type: cross Abstract: Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading model

Safety

AlignFace: Human-Aligned Face Similarity Metric with Interpretable Concept Relations