Search: “context”

CARRE: Counterfactual Action Retrieval and Reason Evaluation for Explainable Churn Prescription

arXiv:2609.09766v1 Announce Type: new Abstract: Churn models typically identify high-risk customers but do not specify which feasible retention action should be considered or why that action is approp

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Local Ai

CyberTiel 35B-A3B’s uncensored 4-bit quant beats Opus 4.6 medium cleanly on real codebase issues, in 27% of the time Qwen3.8-27b medium takes.

DGX agent

The downside of uncensoring a model is that it is known to potentially damage it, but CyberTiel is an even more capable software engineer than its censored TielCoder base, while allowing offensive sec

local-air-localllama

10 Sept 2026

Detokenization Leaks: Reconstructing Local LLM Outputs From Cache Traces

arXiv:2609.06674v1 Announce Type: cross Abstract: We present a new attack that reconstructs the text generated by locally hosted LLMs by observing CPU cache activity during detokenization. Unlike prio

DiSCo: A Distribution-First Steering and Cultural Prior Evaluation Framework for Measuring Cultural Preference Bias in LLMs

arXiv:2609.10253v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in globally used assistants, yet their default choices in culturally grounded everyday situations

local-aiarxiv-cs-cl

Distillation of Synthetic Data for Time Series Foundation Models

arXiv:2609.09586v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are increasingly pre-trained on synthetically generated time series trajectories, where the data generating proc

EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval

arXiv:2609.07194v1 Announce Type: new Abstract: We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accura

Evaluating the Scalability and Adversarial Generalization of GRPO-Trained NLI Models

arXiv:2504.18376v3 Announce Type: replace-cross Abstract: Natural Language Inference (NLI) is a central task in natural language understanding with applications in fact-checking, question answering, a

Event Interaction in Low-Rank Bottlenecks for Temporal Relation Extraction

arXiv:2609.06731v1 Announce Type: cross Abstract: Temporal relation extraction determines whether an event occurs before, after, or simultaneously with another event, and therefore relies on accuratel

Exposing Weaknesses in Emotion Recognition in Conversations

arXiv:2609.05806v1 Announce Type: new Abstract: Emotion Recognition in Conversations (ERC) aims to identify speakers' emotions in multi-turn dialogue. Accurate emotion recognition can support a wide r

FreqBLiMP: Frequency-Controlled Minimal Pairs Reveal Robustness and Fragility of LLMs Under Lexical Rarity

arXiv:2609.07153v1 Announce Type: cross Abstract: Minimal-pair benchmarks such as BLiMP evaluate linguistic knowledge by testing whether language models (LMs) prefer acceptable sentences over minimall

From Scores to Evidence: Auditable Decisions Can Improve Speech Deepfake Detection

arXiv:2609.08899v2 Announce Type: replace-cross Abstract: Speech deepfakes can mimic a speaker's voice convincingly enough to deceive listeners and automated systems. This has driven strong progress i

Agents

Graph-Based Personalized Memory for LLM Agents: Representation, Evolution, Retrieval, and Evaluation

arXiv:2609.08599v1 Announce Type: new Abstract: Large Language Model (LLM) agents are evolving from single-session tools toward long-term personal assistants that must adapt to individual users across

agentsarxiv-cs-ai

Human mutation field reveals an equilibrium-like structure with irreversible circulation

arXiv:2609.07500v1 Announce Type: cross Abstract: The evolution of DNA sequences can be viewed as stochastic dynamics on a high-dimensional discrete space, but it is unclear when empirical transition

Information entropy as an anthropomorphic concept

arXiv:1503.01967v3 Announce Type: replace-cross Abstract: According to E.T. Jaynes and E.P. Wigner, entropy is an anthropomorphic concept in the sense that in a physical system correspond many thermod

Limits of Reliability and Scaling in Language Models

arXiv:2607.14112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained and evaluated as though perfect reliability is achievable for any task given sufficient scale. We sho

LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation

arXiv:2609.10239v1 Announce Type: cross Abstract: Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversiz

Literati: Towards Anytime Optimal Shape Generalized Trees via AO*

arXiv:2609.09299v1 Announce Type: new Abstract: Decision trees are prized for their interpretability and strong performance on tabular data, but popular greedy top-down induction algorithms can yield

safetyarxiv-cs-lg

LLM-Generated or Human-Written? Comparing Review and Non-Review Papers on ArXiv

arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of L

safetyarxiv-cs-cl

Agents

MeClear: Cooperative Game-Theoretic Attribution and Risk-Aware Memory Clearance for Long-Horizon LLM Agents

arXiv:2609.09115v1 Announce Type: new Abstract: Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interacti

agentsarxiv-cs-ai

MLLMs Hallucinate when Information Distribution Drifts in Synergy Heads

arXiv:2609.09206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) often struggle with hallucinations, thus hindering their reliable practical applications. Existing attention-

ObGynLongBench: Revealing the Evidence-to-EHR Gap in Longitudinal EHR Decision-Making

arXiv:2609.07601v1 Announce Type: cross Abstract: The application of large language models (LLMs) to personalized medical assistants has garnered growing interest. However, existing medical benchmarks

OntologyAligner: Ontology-Aligned Retrieval and Hierarchy-Guided Large Language Model Reranking for Biomedical Ontology Normalization

arXiv:2609.10055v1 Announce Type: cross Abstract: Biomedical ontology normalization maps free-text expressions to standardized concepts, enabling consistent integration and analysis of biomedical data

Positional task conditioning for scalable defect detection across product families in large product catalogs

arXiv:2609.09567v1 Announce Type: new Abstract: Product families in large product catalogs suffer from inconsistencies such as duplicates and unit mismatches that degrade customer experience. Detectin

Qwen-Audio-3.0-ASR Technical Report

arXiv:2609.07549v2 Announce Type: replace Abstract: In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling,

Hardware

RAGMark: A Comprehensive Framework for Benchmarking Retrieval-Augmented Generation Systems

arXiv:2609.05760v1 Announce Type: cross Abstract: We present RAGMark, a modular benchmarking framework for advanced Retrieval-Augmented Generation (RAG) systems targeting small-scale multi-GPU environ

hardwarearxiv-cs-ai

SalamandraTA at WMT 2026 Terminology Shared Task: Hard Examples Are Better Teachers

arXiv:2609.09999v1 Announce Type: new Abstract: Terminology-aware translation asks for more than a correct translation: the output must use the exact terms a glossary prescribes. The standard recipe,

Same Values, Different Languages? From Multilingual Probing to Steering LLMs Toward Chinese Social Values

arXiv:2609.08515v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into human society, aligning them with pluralistic social values has become a critical pri

safetyarxiv-cs-ai

Scratchy: Visual-Scratchpad Multimodal Reasoning for Cryptographic Proof Generation in EasyCrypt

arXiv:2609.06226v1 Announce Type: cross Abstract: Large language models (LLMs) have recently made substantial progress in formal proof generation, yet presenting distinctive challenges in cryptographi

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

Settling: Equilibrium Inference for Non-Convex Validity Sets

arXiv:2609.09682v1 Announce Type: new Abstract: Many learning systems return a single point estimate even when admissible outputs form disconnected or non-convex sets. Under squared loss, an ambiguous

SkillSpec: Intent-Masked Specification Reasoning for Agent Skill Correctness

arXiv:2609.06052v1 Announce Type: cross Abstract: Autonomous agent systems increasingly depend on reusable skill abstractions for consolidating experiential knowledge and domain expertise. These artif

Applications

Solving versus Verifying: Catching Contradictions in Tax Reasoning Systems

arXiv:2609.05928v1 Announce Type: cross Abstract: Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for th

applicationsarxiv-cs-ai

Steering Diffusion Priors with Sparse Observations for High-Resolution Temperature Downscaling

arXiv:2609.09247v1 Announce Type: cross Abstract: Local heatwave hazard depends on fine-scale air temperature, but ground stations are sparse and reanalysis products such as ERA5 cannot resolve the te

local-aiarxiv-cs-lg

Structure-Aware Unsupervised Anomaly Detection for Spacecraft Telemetry with Adaptive EVT Thresholding

arXiv:2609.10017v1 Announce Type: new Abstract: Operational anomaly detection in spacecraft telemetry typically requires labeled historical anomalies or extended warm-up periods. These requirements ar

Applications

Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks

arXiv:2505.03380v2 Announce Type: replace Abstract: Accurate delineation of tumors and surrounding organs-at-risk is essential for radiotherapy, surgery and treatment response assessment, yet remains

applicationsarxiv-cs-cv

View-Structured Conformal Prediction for 3D Gaussian Splatting

arXiv:2609.10307v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) renders novel views in real time, but an uncertainty heatmap does not certify that a rendered view meets a certain predic

researcharxiv-cs-cv

When and Why LLM Causal Priors Help: Closed-Loop Prior Selection for Amortized Causal Inference

arXiv:2609.06941v1 Announce Type: new Abstract: Causal effect estimation asks how an outcome would change under an intervention, and medicine, economics, and public policy all treat it as a foundation

When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors

arXiv:2609.09887v1 Announce Type: new Abstract: LLMs have been used to simulate human decision-making in professional settings, yet their behaviors in common-law jury trials remain unexplored. We stud

When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents

arXiv:2609.05441v1 Announce Type: new Abstract: Long-term memory for LLM agents is evaluated today by conversational recall benchmarks (LoCoMo, LongMemEval), which measure question answering over dial

When Fusion Fails: Corruption-Aware Rebalanced Fusion for Multi-Modal Medical Image Segmentation

arXiv:2609.10261v1 Announce Type: new Abstract: Multi-modal medical image segmentation leverages complementary diagnostic information, yet fusion can underperform single-modality baselines when spatia

safetyarxiv-cs-cv

When Tools Hurt LLM Reasoning: State-Dependent Belief Revision under External Evidence

arXiv:2508.15754v2 Announce Type: replace-cross Abstract: Tool use is often assumed to monotonically improve reasoning, where external evidence is expected to help when relevant and be ignored when ir

Who Argues What? Joint Argument-Entity Detection and Classification in Political Debates

arXiv:2609.10192v1 Announce Type: new Abstract: Political debates are often analyzed through Argument Mining (AM) to investigate the key arguments that drive them. However, political arguments are rar

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

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

model-releasesarxiv-cs-cv

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

Cadence: Error-Bounded Lossy Compression of Demand Time Series with a Time-Series Foundation Model

model-releasesarxiv-cs-lg

arXiv:2609.06008v1 Announce Type: cross Abstract: We present Cadence, an error-bounded lossy compressor for numeric time series pairing a 330M-parameter time-series foundation model (Google TimesFM-3)

ChatBEV: Empowering Traffic Scene Understanding and Simulation via Vision-Language Model

model-releasesarxiv-cs-cv

arXiv:2503.13938v3 Announce Type: replace Abstract: Comprehensive traffic scene understanding is a foundational capability for Intelligent Transportation Systems (ITS) underpinning applications such a

Tutorials

Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRI

arXiv:2609.06807v1 Announce Type: new Abstract: In this work, we comprehensively evaluate three popular feature-extraction paradigms in AI-based neuroimaging modeling: (1) computation of anatomical su

tutorialsarxiv-cs-cv

CrossModalQA: A Cross-modal and Multi-hop Benchmark for Multimodal Retrieval-augmented Generation

model-releasesarxiv-cs-cv

arXiv:2609.05518v1 Announce Type: new Abstract: Despite the strong capabilities of multimodal large language models (MLLMs), their parametric knowledge remains incomplete and difficult to update, moti