Search: “llm”

arXiv:2608.08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows. H

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How Do Large Language Models Judge Social Attraction? Evidence from Theory-Grounded Persona Ratings Across Multiple LLMs and Humans

DGX agent

arXiv:2608.09717v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to perform subjective evaluations traditionally made by humans, yet their validity as social judges

researcharxiv-cs-ai

11 Aug 2026

MateInfoUB: A Real-World Benchmark for Testing LLMs in Competitive, Multilingual, and Multimodal Educational Tasks

arXiv:2507.03162v2 Announce Type: replace-cross Abstract: The rapid advancement of Large Language Models (LLMs) has transformed various domains, particularly computer science (CS) education. These mod

NeuPAT: Neuron-aware Plasticity Allocation Tuning for Language-Preserving MLLMs

arXiv:2608.08107v1 Announce Type: cross Abstract: Multimodal expansion of large language models (LLMs) enables new perceptual capabilities but often compromises the language intelligence acquired duri

Prompt Embedding Probes (PEP): Hallucination Detection in LLMs from Hidden States

arXiv:2608.08024v1 Announce Type: cross Abstract: Large language models (LLMs) can generate fluent and useful responses but remain prone to hallucinations. We introduce Prompt Embedding Probes (PEP),

Right Answer, Wrong Heat: Explanation-Aware Evaluation and Thermal-Grounded Feedback for MLLMs on Infrared Images

arXiv:2608.09145v1 Announce Type: new Abstract: General-purpose multimodal large language models (MLLMs) are increasingly applied to infrared images, where they are commonly scored by answer accuracy

researcharxiv-cs-cv

Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents

arXiv:2601.18077v3 Announce Type: replace Abstract: Cooperative reasoning under incomplete information remains challenging for both humans and multi-agent systems. The card game Hanabi embodies this c

SymboUQ: Symbolic Uncertainty Quantification for Spatial Reasoning in LLMs

arXiv:2608.00417v2 Announce Type: replace Abstract: Although large language models (LLMs) can produce fluent spatial reasoning traces, their intermediate relations may fail to support the final conclu

When Grammar Guides the Attack: Uncovering Control-Plane Vulnerabilities in LLMs with Structured Output

arXiv:2503.24191v4 Announce Type: replace-cross Abstract: Content Warning: This paper may contain unsafe or harmful content generated by LLMs that may be offensive to readers. Large Language Models (L

Can Language Models Imagine Without Seeing? Ekphrasis: Measuring Visual Creative Ideation in Text-Only LLMs

arXiv:2608.06967v1 Announce Type: new Abstract: Current evaluations do not isolate whether text-only language models can originate visual concepts before image generation. Fluent visual prose can hide

10 Aug 2026

GeoBenchLLM: A Comprehensive Benchmark for Evaluating LLMs on Geo-Related Tasks

arXiv:2608.07411v1 Announce Type: new Abstract: In the context of geodata, existing Large Language Models have often been studied in a homogeneous setting, which has considerably limited insights into

10 Aug 2026

Grammar Engineering Meets LLMs: Development of Cantonese and Irish ParGram Treebanks

arXiv:2608.07283v1 Announce Type: new Abstract: Grammar engineering requires expertise in linguistic formalism and computational implementation, especially in parallel grammar projects that balance cr

10 Aug 2026

As You Wish: Mission Planning with Formal Verification using LLMs in Precision Agriculture

arXiv:2606.18519v2 Announce Type: replace-cross Abstract: Though robotic systems are now being commercialized and deployed in various industries, many of these systems are highly specialized and often

safetyarxiv-cs-ai

Can Open-Weight LLMs Produce Kernel-Verified Coq Proofs? A Pilot Study

model-releasesarxiv-cs-lg

arXiv:2608.05420v1 Announce Type: cross Abstract: Large language models (LLMs) can generate text that resembles a mathematical proof, but resemblance does not establish correctness. A formal proof che

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery?

arXiv:2608.06022v1 Announce Type: new Abstract: Epitopes determine where antibodies bind antigens and shape downstream therapeutic properties such as functional blockade and escape resistance, making

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

arXiv:2608.06301v1 Announce Type: new Abstract: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts,

MetaboLLM: a metabolomics-specialized large language model for biochemical knowledge integration and predictive metabolite graph construction

model-releasesarxiv-cs-lg

arXiv:2608.06253v1 Announce Type: new Abstract: Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to translate into predictive representations. We developed Me

Can Post-Training Transform LLMs into Causal Reasoners?

arXiv:2602.06337v2 Announce Type: replace-cross Abstract: Causal inference is essential for decision-making but remains challenging for non-experts. While large language models (LLMs) show promise in

6 Aug 2026

Balancing Efficiency and Efficacy: Training-Free Attention-Guided Switching Between Explicit and Latent Thoughts for MLLMs

arXiv:2608.03450v1 Announce Type: cross Abstract: Reasoning in Multimodal Large Language Models (MLLMs) requires both fine-grained visual perception and rigorous logical deduction. Explicit text-based

Can LLMs Test Terminal User Interfaces?

arXiv:2608.03743v1 Announce Type: cross Abstract: Terminal User Interfaces (TUIs) combine the stateful, screen-oriented behaviour of GUIs with terminal deployment and are now common in developer tools

ConlangBench: Exploring Language Knowledge and Learning in LLMs through Diverse Constructed Languages

arXiv:2608.03505v1 Announce Type: new Abstract: Constructed languages (conlangs) are intentionally created human languages with a rich tradition of linguistic creativity. Despite their potential for s

LLMs Can Annotate Attribution Graphs

arXiv:2608.02632v1 Announce Type: new Abstract: Circuit tracing is an exciting technique for revealing the internal computation of language models, but it requires a time-intensive manual step of grou

researcharxiv-cs-lg

Speech LLMs in Low-Resource Scenarios: Data Volume Requirements and the Impact of Pretraining on High-Resource Languages

arXiv:2508.05149v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated potential in handling spoken inputs for high-resource languages, reaching state-of-the-art perf

When Many Answers Are Valid, Voting Fails: Symbolic Verification for Best-of-K Causal Reasoning in LLMs

arXiv:2608.03506v1 Announce Type: new Abstract: Self-consistency assumes the most frequent answer among sampled reasoning traces is the most reliable, but this can fail in causal reasoning: samples of

Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization

arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical findi

Leveraging Synthetic Data for Question Answering with Multilingual LLMs in the Agricultural Domain

arXiv:2507.16974v3 Announce Type: replace Abstract: Enabling farmers to access accurate agriculture-related information in their native languages in a timely manner is crucial for the success of the a

MedPRESS: A Multi-turn Benchmark for Patient-Pressure-Induced Medical Sycophancy in LLMs

arXiv:2608.02520v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for health-related advice. Existing research measures their safety with static questions rather than

Mitigating Visual Degradation in MLLMs via Spatial-Spectral Visual Anchor Learning

arXiv:2608.01635v1 Announce Type: new Abstract: Despite the progress of multimodal large language models (MLLMs), they continue to exhibit deficiencies in visual perception. Following visual instructi

safetyarxiv-cs-cv

SG-Layout: Structured Scene Graph-Guided Layout Generation with LLMs

arXiv:2608.01106v1 Announce Type: new Abstract: Understanding and generating spatially coherent layouts from natural language remains a fundamental yet challenging task for large language models (LLMs

safetyarxiv-cs-cv

Knowing When to Quit: Diagnosing and Training LLMs to Abort Futile Reasoning

arXiv:2607.29211v1 Announce Type: new Abstract: Large language models generate computationally expensive yet semantically void reasoning on beyond-capability tasks, creating risks where plausible-soun

3 Aug 2026

Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering

arXiv:2607.28906v1 Announce Type: new Abstract: Sycophancy refers to the tendency for large language models (LLMs) to match user beliefs at the cost of factual correctness, thereby undermining model r

3 Aug 2026

HARGO: Heterogeneity-Aware Reward-Guided Optimization for RL Post-Training of LLMs on HPC Tasks

model-releasesarxiv-cs-lg

arXiv:2607.28301v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) can equip large language models (LLMs) with domain knowledge for high-performance computing (HPC) tasks such as data race d

31 Jul 2026

HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs

arXiv:2607.27379v1 Announce Type: new Abstract: High-quality, diverse data are vital for large language models (LLMs) but remain scarce and costly. Data synthesis is a viable alternative and succeeds

safetyarxiv-cs-cl

31 Jul 2026

LAST: The Last Query Token Guides Visual Token Pruning for Edge-Cloud Collaborative MLLM Inference

arXiv:2607.27952v1 Announce Type: new Abstract: Multimodal foundation models are reshaping edge-cloud visual intelligence from task-specific feature pipelines into token-based interfaces, where edge d

researcharxiv-cs-cv

31 Jul 2026

DialectLLM: A Dialect-Aware Dialog[ue] Generation Framework Beyond Standard American English

arXiv:2601.22888v4 Announce Type: replace Abstract: More than 80% of the 1.6B English speakers do not use Standard American English (SAE), yet LLMs often fail to correctly identify non-SAE dialects an

30 Jul 2026

Prosody-driven Jailbreaks in Audio LLMs: A Controlled Study and Mechanistic Analysis

arXiv:2607.26541v1 Announce Type: cross Abstract: Audio-capable foundation models enable end-to-end spoken interaction, but they also introduce safety risks beyond transcript content. It remains uncle

30 Jul 2026

CARE-MH: Towards Unified, Reproducible, and Comparable Evaluation of Mental Health LLMs

arXiv:2607.24754v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to provide mental health support, requiring reliable evaluation of safety, empathy, and therapeutic

29 Jul 2026

Localizing Persona Representations in LLMs

arXiv:2505.24539v4 Announce Type: replace-cross Abstract: We present a study on how and where personas -- defined by distinct sets of human characteristics, values, and beliefs -- are encoded in the r

29 Jul 2026

Closed-Loop Validation-Repair for Healthcare Interoperability: A Multi-Model Study of Schema Compliance in Clinical LLMs

arXiv:2607.24371v1 Announce Type: cross Abstract: Healthcare interoperability requires AI systems to produce structured outputs conforming to standardized schemas including ICD-10 for diagnostic codin

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs

arXiv:2607.22577v1 Announce Type: new Abstract: Scaling large language models (LLMs) has driven their success, yet dense Transformers couple capacity and computation: every parameter is activated for

Applications

Farm-LightSeek: An Edge-centric Multimodal Agricultural IoT Data Analytics Framework with Lightweight LLMs

arXiv:2506.03168v2 Announce Type: replace Abstract: Amid the challenges posed by global population growth and climate change, traditional agricultural Internet of Things (IoT) systems is currently und

applicationsarxiv-cs-cv

Revitalizing Public Urban Places through Cultural and Political Memory: A Technological Approach with LLMs and Augmented Reality

arXiv:2607.22613v1 Announce Type: cross Abstract: This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate thi

Applications

TRACE: Business Rule-Grounded Reasoning Curriculum for Knowledge-Preserving Parametric Tool Retrieval in Enterprise LLMs

arXiv:2607.22639v1 Announce Type: new Abstract: Parametric retrieval enables LLMs to retrieve tools implicitly by assigning each API a unique virtual token and training the model to generate it via co

applicationsarxiv-cs-ai

Zing: Social Mind for LLMs

arXiv:2607.23740v1 Announce Type: new Abstract: As large language models move from isolated task solving toward long-term service in human environments, they require social intelligence: the ability t

Adaptive Depth Sparse Framework: Similarity-Driven Resource Allocation for Pre-Trained LLMs

arXiv:2607.21291v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong generation and reasoning performance, but the Transformer architecture incurs high inference cost. Existing

safetyarxiv-cs-cl

24 Jul 2026

Tutorials

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

arXiv:2607.21076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantizatio

tutorialsarxiv-cs-cv

24 Jul 2026

Robust Critics: Defending LLMs Against Multi-Turn Attacks

arXiv:2607.20472v1 Announce Type: new Abstract: When a user asks a language model something harmful, is it a genuine attack or a misunderstood but well-meaning question? This ambiguity is one of the c

safetyarxiv-cs-ai

24 Jul 2026

Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation: A Comparative Study

arXiv:2502.16022v3 Announce Type: replace Abstract: OpenNotes gives patients access to their EHR notes, but dense medical jargon limits comprehension. We evaluate closed-source and open-source LLMs fo