Search: “llm”

RAG4Tickets: AI-Powered Ticket Resolution via Retrieval-Augmented Generation on JIRA and GitHub Data

arXiv:2510.08667v3 Announce Type: replace-cross Abstract: Modern software teams frequently encounter delays in resolving recurring or related issues due to fragmented knowledge scattered across JIRA t

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Model Releases

Same Answer, New Box: How Much of RLVR's Out-of-Domain Gain Is Answer Format?

DGX agent

arXiv:2610.20639v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is credited with gains beyond the domain its rewards check, such as higher MMLU accuracy after t

model-releasesarxiv-cs-cl

16 Oct 2026

Applications

Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as

applicationsarxiv-cs-lg

Towards Emotion Consistency Analysis of Large Language Models in Emotional Conversational Contexts

arXiv:2605.06476v2 Announce Type: replace Abstract: In this work, we conduct an analysis to examine the consistency of Large Language Models (LLMs) with respect to their own generated responses in an

TRACER: A Multimodal Harness for Patient Care in Hospitals

arXiv:2610.21266v1 Announce Type: cross Abstract: Continuous video and clinical records provide complementary information for understanding how patient behavior evolves over a hospital stay. A central

Training Reasoning Models to Generate Diverse Scientific Ideas

arXiv:2610.22324v1 Announce Type: new Abstract: One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of

Twice Upon a Time: Complementary Representations for Time-Series Reasoning

arXiv:2610.22327v1 Announce Type: cross Abstract: Time Series Language Models (TSLMs) enable language-based understanding and reasoning over temporal data, yet a fundamental question remains: what inf

V-SHARE: Provable Convergence Guarantees for Advantage-based Algorithms

arXiv:2610.21448v1 Announce Type: cross Abstract: In reinforcement learning, advantage-based value-learning methods, unlike standard Q-learning, share information across actions by decomposing the act

Volition Elicitation: Operational Semantics for People and Their Machines

arXiv:2607.14138v2 Announce Type: replace-cross Abstract: The most prevalent distributed systems today include people and their personal machines (smartphones), and computations in them are driven by

Who May Release an Agent's Promise? Standing over Commitments in Multi-Party Chat

arXiv:2610.21203v1 Announce Type: new Abstract: When an assistant serving a team makes a promise to Alice, who may cancel it? We call this standing: only the creditor (the person owed) or someone the

Wolof-Adapted Industry-Ready Open-Weight Language Models

arXiv:2610.20824v1 Announce Type: cross Abstract: Wolof is spoken by 23M people, mostly in Senegal, but remains weakly supported by open-weight language models, while API models raise cost, governance

local-aiarxiv-cs-ai

ActMOF: Mapping Reticular Synthesis through Active Learning

model-releasesarxiv-cs-lg

arXiv:2610.19404v1 Announce Type: cross Abstract: Reticular chemistry allows metal-organic frameworks (MOFs) to be designed from their building units, yet their synthesis remains constrained by sparse

Hardware

AdaRSI: On-Demand Recursive Self-Improvement for Embodied Agents

arXiv:2610.20474v1 Announce Type: new Abstract: Pretrained vision-language-action models (VLAs) often fail midway through unseen long-horizon tasks. Recursive self-improvement (RSI) offers a remedy, b

hardwarearxiv-cs-cl

AegisVox: Factorized Privacy and Clinical Preservation for Long-Form Speech

arXiv:2610.14643v1 Announce Type: new Abstract: Clinical speech reveals identity through both spoken identifiers and voice, yet its pauses, delivery, and speaker roles can also carry useful clinical e

AlignMerge - Alignment-Preserving Large Language Model Merging via Fisher-Guided Geometric Constraints

arXiv:2512.16245v2 Announce Type: replace Abstract: Merging large language models (LLMs) is a practical way to compose capabilities from multiple fine-tuned checkpoints without retraining. Yet standar

ANCHOR: Assessing Naturalistic Constraint Hierarchies and Ordering in Repository-Grounded Agentic Coding

arXiv:2610.16859v2 Announce Type: replace Abstract: For repository-grounded coding agents, a functionally correct patch is not necessarily an acceptable one: developers also constrain how the task mus

Beyond Aggregate Accuracy: Item-Level Transitions in Prompt Optimization

arXiv:2610.19084v1 Announce Type: cross Abstract: Automatic prompt optimization (APO) uses feedback from model responses to improve prompts automatically. However, its effectiveness is usually measure

Beyond Reward Engineering: A Data Recipe for Long-Context Reinforcement Learning

arXiv:2606.18831v2 Announce Type: replace-cross Abstract: Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that mus

Beyond the Verdict: Agentic Code Judging with Verifiable Feedback

arXiv:2610.18760v1 Announce Type: new Abstract: Test-time scaling for large language models (LLMs) can involve generating multiple candidate solutions for selection or revising an earlier attempt. To

Big-Big-SycoBench: A Benchmark to Detect Sycophancy Through Model Responses to Valid vs. Invalid Arguments

arXiv:2610.15634v1 Announce Type: new Abstract: Sycophancy in large language models risks amplifying unsupported claims or beliefs across the knowledge ecosystem as these systems increasingly contribu

CAFE: Confining Feature Distillation to Language-Routed Adapters for Compact Multilingual Automatic Speech Recognition

arXiv:2610.19134v1 Announce Type: new Abstract: Feature distillation is usually expected to add to logit distillation. We find that this expectation does not hold for two common feature losses in comp

safetyarxiv-cs-cl

Can Generative AI Automate Data Extraction for Meta-Analysis? A Case Study on Intercropping Research

arXiv:2609.35089v2 Announce Type: replace Abstract: Meta-analysis is the synthesis of information from multiple sources to arrive at an overarching conclusion. There is a large need for meta-analysis

Can You Trust Your Preference Models? Stackelberg Games for Alignment

arXiv:2610.15008v1 Announce Type: new Abstract: Language models are frequently aligned to human preferences via imperfect evaluators whose errors can be exploited during optimization. We train policie

Choosing the Number of Attention Heads from Intrinsic Dimension: A Small-Scale Study

arXiv:2610.19966v1 Announce Type: new Abstract: The number of attention heads in a transformer is usually set by convention or grid search. We test a simple heuristic for setting it in advance: estima

claimcheck: Measuring and Improving Specification Faithfulness

arXiv:2610.17358v1 Announce Type: cross Abstract: Formal verification proves that a program satisfies its specification, but says nothing about whether the specification captures what the author meant

CLIVO: Differentiable Cluster-Based Instruction Mixing with Learned Validation Objectives

arXiv:2610.16876v1 Announce Type: new Abstract: Target-aware multimodal instruction selection requires useful examples and an appropriate balance of supervision. Sample-level rankings can overrepresen

CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image Generation

model-releasesarxiv-cs-cv

arXiv:2610.20603v1 Announce Type: new Abstract: We present CommerceGen-Studio, an end-to-end framework for generating commercial-grade main images for e-commerce Stock Keeping Units (SKUs). Our framew

Computational Reflective Equilibrium for Agentic AI: A Rawlsian Alignment Scaffold for Governance

arXiv:2610.16015v1 Announce Type: new Abstract: The rapid deployment of agentic AI has introduced complex challenges for the ethics and governance of AI systems. Agents built on large language models

Cortex: Consolidating Context into Parametric Memory

arXiv:2610.20399v1 Announce Type: new Abstract: Context can improve large language model performance, but these gains may be lost after context removal. Inspired by biological systems consolidation, w

Crossing the Gender Binary: Modelling Gendered Reference in Science Fiction and General Fiction

arXiv:2610.19028v1 Announce Type: new Abstract: Science fiction is widely credited with unsettling gender. This article asks whether that holds at the linguistic level, in how readily gendered referen

CWE-bench: Refocusing Agentic Security from Exploitation to Defense

arXiv:2610.17020v1 Announce Type: cross Abstract: Cybersecurity evaluations of AI agents have focused largely on offense, yet a working exploit does not show that an agent can make software safe. An a

DAGFormer: Global Topology Prediction for Transformer Cross-Layer Connections

arXiv:2610.19625v1 Announce Type: new Abstract: We propose DAGFormer, a Transformer language model whose cross-layer connections are planned by a jointly trained topology predictor. Beyond the residua

Hardware

DEEPRUBRIC: Evidence-Tree Rubric Supervision for Efficient Reinforcement Learning of Deep Research Agents

arXiv:2606.17029v2 Announce Type: replace Abstract: Deep research agents synthesize long-form reports by searching and reasoning over retrieved evidence. Reinforcement learning with rubric-based rewar

hardwarearxiv-cs-cl

Diagnosing and Correcting Reward Hacking in Verifiable Instruction Following

arXiv:2610.19525v1 Announce Type: cross Abstract: Verifiable instruction-following benchmarks emphasize output-constraint satisfaction but can overlook whether responses meaningfully answer the underl

Diff Diffusion: Predicting Edit Paths with Diffusion Models for Efficient Code Editing

arXiv:2610.17831v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are appealing for code generation because they can update many tokens in parallel, yet many are optimized for

local-aiarxiv-cs-ai

Efficient contextual partial monitoring with general function approximation

arXiv:2610.19804v1 Announce Type: new Abstract: We study finite stochastic partial monitoring (PM) games with side information, a paradigm of sequential learning with partial feedback. On each round t

local-aiarxiv-cs-lg

Efficiently Learning To Reason or Not to Reason: Root-token Policy Optimization for Adaptive Thinking

arXiv:2610.17767v1 Announce Type: cross Abstract: Large reasoning models (LRMs) achieve strong performance by externalizing explicit reasoning traces before producing the answer, yet suffer from overt

local-aiarxiv-cs-ai

Encounter-Driven City-Scale Human Mobility Generation with Large Language Models

arXiv:2610.17672v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for human mobility generation by modeling individual routines, activities, and mobility prefere

Equal CER, Unequal Damage: Severity-Weighted Character Error Rate for OCR

arXiv:2610.20461v1 Announce Type: new Abstract: Character Error Rate (CER), the standard metric for OCR and vision-language models (VLMs), charges a typo as much as a wrong name. We introduce semCER,

safetyarxiv-cs-cl

Evaluating Compressed Memory: Dependence, Utility, and Content Benefit

arXiv:2610.19373v1 Announce Type: new Abstract: Does a language model answer better because its compressed memory contains useful document information? Replacing memory vectors with zeros can lower a

Evaluating Large Language Models for Multilingual Abstractive Summarization: A Comprehensive Study of English and Bengali

arXiv:2610.19003v1 Announce Type: new Abstract: Abstractive summarization remains challenging across languages, where linguistic quality and factual consistency may diverge, particularly in low-resour

Fewer Bits, More Tries: Recovering Capability Under Memory Constraints

arXiv:2610.15372v1 Announce Type: new Abstract: Large language models are generally more capable than smaller ones, but their memory requirements can make local deployment difficult. We ask whether pa

From Failures to Learnable Worlds: Policy-Conditioned Environment Generation for Navigation Agents

model-releasesarxiv-cs-cv

arXiv:2610.19420v1 Announce Type: cross Abstract: Simulated environments enable scalable training data generation for embodied agents, but more data does not necessarily provide what a particular agen

From Individuals to Interactions: Benchmarking Gender Bias in Multimodal Large Language Models from the Lens of Social Relationship

arXiv:2506.23101v2 Announce Type: replace-cross Abstract: Ensuring the trustworthiness of Multimodal Large Language Models (MLLMs) requires rigorous evaluation of gender bias, particularly in socially

Frustratingly Easy Agentic RAG via Portable Skills: A Case Study in Customer Support

arXiv:2610.14428v1 Announce Type: new Abstract: Enterprise workflow automation typically requires retrieving a complete and accurate set of relevant information from large operational document corpora

GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?

arXiv:2610.15129v1 Announce Type: new Abstract: Human social perception is incremental: we infer intent before an utterance is complete, revise our interpretation as new cues arrive, and attend to spe

Governing Copyright Responsibly in the Era of Generative AI

arXiv:2610.17002v1 Announce Type: cross Abstract: Large language models are trained on collections that may include scholarly works, while authors generally lack work-level information about whether a

Graph-free Retrieval with Graph-Modified Embeddings

arXiv:2610.18410v1 Announce Type: cross Abstract: Dense vector retrieval can miss evidence connected through intermediate entities, while direct graph retrieval requires access to the graph at query t