Search: “model-releases”

RePro: Proof-Verified Benchmark Rewriting for Reliable Evaluation of LLM Mathematical Problem Solving

arXiv:2609.00062v1 Announce Type: cross Abstract: Data contamination undermines the reliable evaluation of large language models (LLMs) on mathematical problem solving. While rewriting-based evaluatio

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ReproRepo: Scaling Reproducibility Audits with GitHub Repository Issues

DGX agent

arXiv:2606.18237v2 Announce Type: replace-cross Abstract: Reproducing research results from papers and released code is central to scientific progress. Existing works have introduced benchmarks to eva

model-releasesarxiv-cs-ai

2 Sept 2026

Residual Sparsification via Output Importance for Compressing Mixture-of-Experts LLMs

arXiv:2609.00575v1 Announce Type: new Abstract: Mixture-of-experts (MoE) architectures scale large language models efficiently, but they demand massive GPU memory. To cope with such demand, models are

RestoreBench: Can AI Agents Restore Power Flow Convergence?

arXiv:2609.00384v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly automate multi-step engineering workflows through tool use, interpretation of intermediate results, and i

Retrieval, Scoring, and Decoding Shape Performance and Stability in LLM-based Conversational Recommendation

arXiv:2609.00086v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as rerankers in conversational recommender systems, yet measured gains depend strongly on the retri

Retrieved but not ranked: surface-form bias in structural retrieval, from mathematics to agent trajectories

arXiv:2609.01556v1 Announce Type: cross Abstract: We evaluate embedding retrieval where surface form and meaning are pulled apart on purpose: retrieving items that share underlying structure but not w

Revealing Multi-View Hallucination in Large Vision-Language Models

arXiv:2603.23934v2 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) are increasingly being applied to multi-view image inputs captured from diverse viewpoints. Despite this

Revisiting Cross-View Completion: Self-Supervised Pre-Training via Reconstruction Error Comparison

arXiv:2609.01530v1 Announce Type: new Abstract: Self-supervised pre-training via cross-view completion learns strong features for 3D vision from co-visible regions of image pairs. However, the referen

Revisiting Face Recognition for Monozygotic Twins: The Celeb Twins Test Set

arXiv:2609.01141v1 Announce Type: cross Abstract: Past literature on face recognition for monozygotic (('identical') twins points to facial marks and mirror asymmetry as possible directions for improv

RPCBench: A Benchmark for Proactive Premise Critique in LLM-based Recommendation

arXiv:2609.00918v1 Announce Type: new Abstract: Large language models are increasingly used as interactive recommender assistants. Their evaluation should therefore go beyond plausible item recommenda

RW-LoRA: Communication-Efficient Decentralized LoRA Fine-Tuning via Random Walks

arXiv:2609.00078v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning methods such as LoRA have become a standard approach for adapting large foundation models. Adopting fine-tuning to dis

SAGE: State-Grounded, Abstention-Aware Evaluation of Task-Oriented Dialogue Agents

arXiv:2609.00434v1 Announce Type: new Abstract: Evaluating task-oriented dialogue agents requires judging not merely whether a reply reads well but whether each turn advances the underlying workflow s

SAM3-LoRA: Parameter-Efficient Adaptation of a Concept-Promptable Foundation Model for Multi-Class Structural Defect Segmentation

arXiv:2609.00469v1 Announce Type: new Abstract: Promptable segmentation foundation models such as SAM3 accept an open-vocabulary text concept and return every instance matching it, but adapting them t

Same Request, Different Boundary: Evaluating Cybersecurity Assistance across Conversational Contexts

arXiv:2609.00578v1 Announce Type: new Abstract: Large Language Models (LLMs) can solve complex problems, but their misuse in high-risk domains can lead to severe consequences. Model providers therefor

Scene Graph-based Driving Scenario Extraction for Automotive Egocentric Datasets

model-releasesarxiv-cs-ro

arXiv:2609.00333v1 Announce Type: new Abstract: Extracting scenarios from unlabelled real-world sensor data streams is a critical but challenging task in the development process of automated driving s

SciTrue: Reliable Scientific Claim Validation with Frontier and Open Language Models at the NTCIR SciClaimEval Task

arXiv:2609.00654v1 Announce Type: new Abstract: We describe the SciTrue team's participation in both subtasks of the NTCIR-19 SciClaimEval task~ite{sciclaimeval}, which asks systems to verify scientif

SDARE-Bench: Evaluating Large Language Models on Conversational Stigma Detection and Response in Dyadic and Group Dialogue

arXiv:2609.01548v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in advice seeking and decision making that may affect social judgements. Despite stigma's profound ef

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

arXiv:2504.01547v3 Announce Type: replace Abstract: Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-s

Separating perception from reasoning in vision-language models: a model-free render ceiling for crystal structures

arXiv:2609.00663v1 Announce Type: new Abstract: Multimodal evaluations cannot say whether a vision-language model misread an image or misreasoned about it, because every existing method for separating

Sierpinski--Knopp Wasserstein Distance for Persistence Diagrams and Applications to 2-Wasserstein Approximation

arXiv:2609.01528v1 Announce Type: cross Abstract: This paper introduces the Sierpinski-Knopp (SK) Wasserstein distance, a fast metric between persistence diagrams. The SK-Wasserstein distance, denoted

Silence is Golden: Mitigating Hallucinations in Large Audio-Language Models via Layer-Weighted Vector Steering

arXiv:2510.12851v2 Announce Type: replace-cross Abstract: Large Audio-Language Models (LALMs) excel in Audio QA but often suffer from hallucinations ungrounded in the audio. To our knowledge, we are t

Simple Additions, Substantial Gains: Expanding Scripts, Languages, and Lineage Coverage in URIEL+

arXiv:2510.27183v3 Announce Type: replace Abstract: The URIEL+ linguistic knowledge base supports multilingual research by encoding languages through geographic, genetic, and typological vectors. Howe

SoK: When Safe Agents Fail Together: The Security of Multi Agent LLM Systems

arXiv:2609.00595v1 Announce Type: cross Abstract: Safe agents can fail together. Multi-agent LLM systems (MAS) move information, state, decisions, and authority across principal boundaries, creating f

Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

arXiv:2609.01279v1 Announce Type: cross Abstract: Emotion is expressed in text along a wide spectrum, from surface lexical cues to inferences entangled with content. Most layer-wise analyses of emotio

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

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection

arXiv:2603.02974v2 Announce Type: replace Abstract: DINO models provide rich patch-level representations that have recently enabled strong performance in unsupervised anomaly detection (UAD). Most exi

Staged Linguistic Seeding: Grounded Query Expansion for Verified-Unit QA in AI Contact Centers

arXiv:2609.00844v1 Announce Type: new Abstract: Customer-service QA in an AI contact center (AICC) runs under deployment constraints that benchmark QA misses: tight voice-hotline latency and a high co

Stochastic Optimization of Tree Tensor Networks

arXiv:2609.00870v1 Announce Type: cross Abstract: Tensor networks, originally developed for quantum many-body physics, are promising models for machine learning. We derive stochastic Riemannian optimi

StudentSim: Training LLM-based Student Simulators

arXiv:2609.01591v1 Announce Type: new Abstract: AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for w

StudyBench: Can Self-Evolution Squeeze Textbooks for Olympiad Capability?

arXiv:2609.00787v1 Announce Type: new Abstract: Humans need to study only a handful of well-written textbooks to master a discipline and attempt its hardest problems. We argue that an ideal self-evolu

Subliminal Learning as Trait-Direction Drift: A Mechanism and Targeted Control under SFT Distillation

arXiv:2609.01091v1 Announce Type: new Abstract: Beyond intended capabilities, model distillation can transfer hidden traits from a teacher. A teacher biased by a system prompt can generate semanticall

Synthetic Worlds for Temporal Evaluation and Knowledge Updating in LLMs

arXiv:2609.00184v1 Announce Type: new Abstract: Large language models (LLMs) rely on static pretraining corpora, causing their knowledge to become outdated over time. Existing approaches for evaluatin

TempCloze: Can Video-LLMs Identify the Missing Middle?

arXiv:2609.01515v1 Announce Type: cross Abstract: Temporal reasoning benchmarks for Video-LLMs are often mediated by language, leaving room for linguistic shortcuts from option wording, answer correla

The Curse of Multilinguality in Lexical Normalization

arXiv:2609.00329v1 Announce Type: cross Abstract: Lexical normalization rewrites the noisy, non-standard words that fill user-generated text (tmrw, u, gr8) into their standard forms. Because labelled

Think Like a Doctor: Conversational Diagnosis through the Exploration of Diagnostic Knowledge Graphs

arXiv:2602.01995v2 Announce Type: replace Abstract: Conversational diagnosis requires multi-turn history-taking, where an agent asks clarifying questions to refine differential diagnoses under incompl

TimeSteer: Inference-Time Speech Scheduling in Joint Audio-Visual Diffusion Models

arXiv:2609.01277v1 Announce Type: cross Abstract: Although pretrained joint audio-visual diffusion models offer rich control over what to generate, they provide no explicit control over when an uttera

Topic Matching in the Wild: Benchmark and Lessons from Real-World ASR Transcripts

arXiv:2609.00330v1 Announce Type: cross Abstract: In contact centers, real-time agent-assist tools determine, for each of many predefined topics, whether a live customer utterance is relevant and disp

TopoAlign: A Framework for Aligning Code to Math via Topological Decomposition

arXiv:2510.11944v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at both informal and formal (e.g. Lean 4) mathematical reasoning but still struggle with autoformalisation,

Towards a Belief-Based World Model for LLM Agents

arXiv:2609.00455v1 Announce Type: new Abstract: Large language models (LLMs) are being used as policies for autonomous decision-making and planning in many domains. Despite their strong reasoning capa

Towards Effective Structured Context Modeling for Conversational Recommender Systems via Dual-node Monte Carlo Tree Search

arXiv:2609.00618v1 Announce Type: cross Abstract: We investigate the role of conversational context modeling in user preference tracking for Conversational Recommendation Systems (CRSs). In this regar

Towards Generalizable Visually Grounded Exploration of Household Devices

arXiv:2609.00845v1 Announce Type: new Abstract: Recent advancements in Vision-Language Models (VLMs) have demonstrated impressive capabilities in static visual recognition and high-level semantic reas

Towards Provable and Scalable Training of Quantized Neural Networks with Ising Optimization

arXiv:2506.18240v5 Announce Type: replace-cross Abstract: Training quantized neural networks remains fundamentally challenging due to non-convex loss landscapes and discrete parameter spaces. We intro

TRIAGE: Three-level Routing and Intelligent Agent Guidance for Efficient Execution

arXiv:2609.01428v1 Announce Type: new Abstract: Large Language Model (LLM) agents based on the ReAct paradigm have demonstrated remarkable capabilities in tool use and task execution. However, ReAct s

Triple-Bottom-Line Sustainability of Language Models for Edge AI: A Comparison Between SLMs and Quantized LLMs

arXiv:2609.00665v1 Announce Type: new Abstract: Edge-AI model selection is commonly driven by one isolated metric - accuracy, latency, memory, energy, or safety, even though a deployable language mode

TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction

arXiv:2609.00832v1 Announce Type: new Abstract: The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery. In this contex

UI-Venus-2 Technical Report

arXiv:2609.00028v1 Announce Type: new Abstract: Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable r

Uncovering the Computational Ingredients of Human-Like Representations in LLMs

arXiv:2510.01030v2 Announce Type: replace Abstract: The human ability to translate diverse perceptual and linguistic inputs into structured behavior has been thought to rest on learning robust represe

Variance-Adaptive Muon: Pre-Orthogonalization Variance Modulation for Efficient Language Model Pretraining

arXiv:2601.14603v2 Announce Type: replace Abstract: Optimizer design plays a central role in efficient language model pretraining, directly affecting optimization dynamics, convergence speed, and comp