News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — NLP / Computation & Language research 2d ago From Structure to Validity: Mechanism-Guided Generation and Refinement of LLM Rubrics arXiv:2610.13375v1 Announce Type: new Abstract: Rubrics have been widely used to evaluate and optimize language models on open-ended tasks. However, existing work primarily focuses on generating better rubrics, with limited understanding of what makes rubric design effective. In… 12 arXiv — NLP / Computation & Language research 2d ago MoPrO-SD: Modular Prompt Optimization for Stance Detection arXiv:2610.13386v1 Announce Type: new Abstract: Stance detection remains challenging for large language models (LLMs) due to implicit opinions, sarcasm, and context-dependent expressions of stance. Although automatic prompt optimization offers an alternative to fine-tuning… 38 arXiv — NLP / Computation & Language research 2d ago Towards the Roof of the World: NLP Progress in Tibetan Languages arXiv:2610.13398v1 Announce Type: new Abstract: Tibetan, spoken by some seven million people on and around the Qinghai-Xizang Plateau, remains underrepresented in natural language processing (NLP). We present, to our knowledge, the first peer-reviewed systematic bibliometric… 7 arXiv — NLP / Computation & Language research 2d ago Towards Enriching Design-Time Models with Evidence from Simulation and Operational Activities arXiv:2610.13456v1 Announce Type: new Abstract: Cyber-Physical Systems are developed through multiple model based activities, comprising several stages of development. As the development progresses through simulation, experimentation, and operation, observations of system… 14 arXiv — NLP / Computation & Language research 2d ago A Better Metric Will Not Save You: What You Compare Beats How You Compare It arXiv:2610.13476v1 Announce Type: new Abstract: Representational similarity measures (RSA, CKA, Procrustes) are chosen for the transformations they treat as irrelevant, and all of them take the set of conditions as given. That set is fixed by two decisions, which inputs are… 29 arXiv — NLP / Computation & Language research 2d ago Proactive Agentic Orchestration arXiv:2610.13485v1 Announce Type: new Abstract: Agentic orchestration delegates tasks to sub-agents with independent contexts, providing a key path to extending the effective execution horizon of large language model agents. However, existing orchestration methods face two… 27 arXiv — NLP / Computation & Language research 2d ago Personalization Without Stereotyping: Do Speech LLMs Know When to Turn a Deaf Ear? arXiv:2610.13550v1 Announce Type: new Abstract: Recent speech LLMs can leverage rich paralinguistic cues, enabling more complex and personalized interactions. However, little work investigates how this sensitivity can lead to stereotyping, and existing evaluations largely… 18 arXiv — NLP / Computation & Language research 2d ago Measuring Artifact Reliance in Machine-Generated Text Detectors arXiv:2610.13583v1 Announce Type: new Abstract: Detectors of machine-generated text score almost perfectly on scientific-literature benchmarks, implying we can reliably distinguish with these detectors human and machine-generated documents. We looked at ten scientific-document… 30 arXiv — NLP / Computation & Language research 2d ago zip2zip++: Towards Inference-Time Token Compression with Minimal Quality Loss arXiv:2610.13605v1 Announce Type: new Abstract: Dynamic vocabularies built on-the-fly via Lempel-Ziv-Welch (LZW) compression let a language model represent the same text in fewer tokens, but prior work shows that this efficiency comes at a cost to reasoning and perplexity. We… 27 arXiv — NLP / Computation & Language research 2d ago BLiMPPI: Benchmark of Linguistic Minimal Pairs for Polarity Items arXiv:2610.13607v1 Announce Type: new Abstract: Negative polarity items (NPIs), such as "anymore" and "ever", are grammatical only in select environments, predominantly in the context of negation. Because their grammaticality depends on both syntax and semantics, they have a… 18 arXiv — NLP / Computation & Language research 2d ago Training User Simulators with Latent Intrinsic Feedback arXiv:2610.13617v1 Announce Type: new Abstract: User simulators are gaining attention as environments to train LLM assistants that can better cope with the nuances of multi-turn conversations with real users. Prior work on user simulation has emphasized generating realistic user… 13 arXiv — NLP / Computation & Language research 2d ago AMLworld-Compact: Importance-Weighted Downsampling for Cost-Effective LLM Evaluation and Error Diagnosis arXiv:2610.13627v1 Announce Type: new Abstract: Evaluating large language models (LLMs) on AMLworld's smallest test splits is costly because each of over a million targets requires a separate graph prompt. Sampling reduces this cost, but small balanced subsets change unweighted… 13 arXiv — NLP / Computation & Language research 2d ago Multi-Stream Attention Residuals arXiv:2610.13630v1 Announce Type: new Abstract: Attention Residuals (AttnRes) enables content-dependent retrieval over network depth, which can be viewed as single-stream softmax attention along the depth axis. Inspired by the success of multi-head attention along the sequence… 9 arXiv — NLP / Computation & Language research 2d ago Inject a Turn, Not a Token: Learning Where to Redirect LLM Reasoning for Self-Correction arXiv:2610.13672v1 Announce Type: new Abstract: Large language models struggle to reliably identify and correct errors in their own reasoning. Unlike prior training-based approaches that fine-tune an LLM to generate revisions or feedback, we learn where to intervene in failed… 19 arXiv — NLP / Computation & Language research 2d ago Retractions Revisited: A Replication, Extension, and Mechanistic Evaluation of Linguistic Obfuscation Effects in Fraudulent Science arXiv:2610.13678v1 Announce Type: new Abstract: Prior work suggests fraudulent scientists write their articles with higher rates of linguistic obfuscation than genuine scientists, with a possible mechanism suggesting obfuscation makes research more costly for a reader to… 30 arXiv — NLP / Computation & Language research 2d ago Verifiable Retrieval for Legal Reasoning through Structure-driven Knowledge Graph arXiv:2610.13695v1 Announce Type: new Abstract: Any automation within reliability-critical contexts such as medicine or law has to be transparent and verifiable. Despite their advantages, current LLM-based systems do not meet these requirements due to their inherent black-box… 32 arXiv — NLP / Computation & Language research 2d ago Enhancing Legal Reasoning in Pre-trained Language Models via Knowledge Graph-Guided Multi-Task Pre-training arXiv:2610.13722v1 Announce Type: new Abstract: Legal language understanding requires reasoning over semi-structured regulatory documents, yet standard pre-training objectives do not explicitly target this structural capability. Because current legal language models rely solely… 8 arXiv — NLP / Computation & Language research 2d ago Not Just an Evaluation: A Case Study of Discourse Particle Sensitivity in Language Models arXiv:2610.13794v1 Announce Type: new Abstract: Discourse particles subtly shape the flow of discourse by reflecting conversational context and interlocutor attitudes, often leaving the truth-conditional meaning untouched. They are also often polyfunctional, with distinct senses… 34 arXiv — NLP / Computation & Language research 2d ago REFLECT: Role-Aware Detection of Sentiment, Emotion, Politeness, and Formality arXiv:2610.13797v1 Announce Type: new Abstract: Detecting communicative meaning in dialogue requires modeling not only lexical content but also the participant-role structures through which sentiment, emotion, politeness, and formality (SEPF) are expressed. Existing approaches… 4 arXiv — NLP / Computation & Language research 2d ago Error Rate is Not Enough: Costs of Augmentation in Low-Resource ASR arXiv:2610.13807v1 Announce Type: new Abstract: Data augmentation is standard practice for low-resource automatic speech recognition (ASR), but its benefits are almost always reported as aggregate error rates, leaving open why and when a method helps. On four low-resource… 18 arXiv — NLP / Computation & Language research 2d ago Can Language Models Learn When to Abstain? Policy Learning and Calibrated Answer Selection arXiv:2610.13821v1 Announce Type: new Abstract: A useful language model should know when to answer and when to say "I don't know." Can we improve that decision by training the model itself or by training a separate component to check its answers? We study both approaches on… 13 arXiv — NLP / Computation & Language research 2d ago Task Context Shapes Component Roles in Language Models arXiv:2610.13895v1 Announce Type: new Abstract: Large language models reuse the same attention heads across tasks, but identifying these shared heads does not explain what they do differently in each task. A natural source of inspiration is task-dependent interactions among… 32 arXiv — NLP / Computation & Language research 2d ago Structural Automata for Neural Semantic Parsing arXiv:2610.13896v1 Announce Type: new Abstract: Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfold during generation. Constrained decoding prevents locally invalid tokens but… 4 arXiv — NLP / Computation & Language research 2d ago When VLMs Destroy What They Know: Spatial Representations Fall Below Lexical Priors arXiv:2610.13910v1 Announce Type: new Abstract: Vision-Language Models (VLMs) increasingly analyze and reason about images, yet it remains unclear whether their internal representations faithfully encode the structured relations required for such reasoning. We introduce EICS… 21 arXiv — NLP / Computation & Language research 2d ago RSI-Anything: Unlocking Recursive Self-Improvement with World Models arXiv:2610.13912v1 Announce Type: new Abstract: Recursive self-improvement (RSI) aims to transform interaction experience into persistent improvements, yet external feedback is costly and world-model predictions may become unreliable as policies evolve. We introduce… 24 arXiv — NLP / Computation & Language research 2d ago SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire arXiv:2610.12596v1 Announce Type: cross Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short and episodic, and performance on long tasks is hard to dissect into stored… 25 arXiv — NLP / Computation & Language research 2d ago Knowing Is Not Telling: Identity Ossification in LLM Representations of Trans-border Communities arXiv:2610.12610v1 Announce Type: cross Abstract: Ethnic and cultural identities rarely align with political borders, a tension made sharper by migration and long-standing cross-border ties. Communities such as the Sami, the Rohingya, and the Kurds have long lived across more… 22 arXiv — NLP / Computation & Language research 2d ago Cancerous Backdoor Attack: Gradual Activation via Invisible Tokens and A Stage Controller arXiv:2610.12644v1 Announce Type: cross Abstract: Backdoor Attacks on Large Language Models (LLMs) typically follow a trigger-response pattern, where satisfying a trigger condition activates a single terminal behavior. However, this single-point backdoor activation does not… 25 arXiv — NLP / Computation & Language research 2d ago Large Language Models, Machine-Assisted Cultural Analytics, and the Agentic Turn arXiv:2610.12792v1 Announce Type: cross Abstract: Technologies like large language models make it easier to convert cultural material into analyzable variables, while LLM-driven agentic systems extend machine assistance to other parts of the research workflow. Rather than a full… 28 arXiv — NLP / Computation & Language research 2d ago VEPA: Verified Evolving Formal Policy for Lifelong LLM Agent Guardrails arXiv:2610.12813v1 Announce Type: cross Abstract: LLM agents increasingly operate over sensitive resources, such as private documents and mutable system states, which can create serious safety and security risks. Runtime guardrails should therefore make inspectable,… 14 arXiv — NLP / Computation & Language research 2d ago MVGraph: Benchmarking LVLMs on Evidence Composition across Multi-View Visual Graph arXiv:2610.12961v1 Announce Type: cross Abstract: We introduce MVGraph, a benchmark for evaluating large vision-language models (LVLMs) on multi-graph reasoning where the evidence required by a query is distributed across multiple interrelated visual graph views. Although such… 31 arXiv — NLP / Computation & Language research 2d ago SmartSalesBench: A Resistance-Aware Multi-Turn Benchmark for Evaluating LLM Sales Agents arXiv:2610.12975v1 Announce Type: cross Abstract: We present SmartSalesBench, the first multi-turn conversational benchmark explicitly designed to evaluate large language model (LLM) sales agents against psychologically grounded, resistant buyer personas. Existing task-oriented… 14 arXiv — NLP / Computation & Language research 2d ago Benchmarking Embedding Geometries and Clustering Algorithms for Unsupervised Patent Claim Classification arXiv:2610.12997v1 Announce Type: cross Abstract: Prior-art retrieval systems are structurally organized around classification codes, making cross-code discovery difficult. This paper asks if an unsupervised representation trained on patent text can recover relevant connections… 37 arXiv — NLP / Computation & Language research 2d ago EmbodiedCLBench: Evaluating Continual Learning for Self-Evolving Embodied Agents arXiv:2610.13021v1 Announce Type: cross Abstract: Continual learning requires models to accumulate past experience and transfer it to new tasks. Despite substantial research on continual learning, existing work remains largely confined to non-embodied settings, without extending… 31 arXiv — NLP / Computation & Language research 2d ago GeoGR: Spatial-Semantic Token Compression and Group Routing for Efficient 3D VLMs arXiv:2610.13035v1 Announce Type: cross Abstract: Multi-view representations enable pretrained image and video vision-language models to understand 3D scenes, but their long visual token sequences make inference costly. Redundancy arises both from repeated observations of the… 6 arXiv — NLP / Computation & Language research 2d ago Travel Back To Move Forward: Retrospective Exploration and Evolving for Long Horizon Agents arXiv:2610.13058v1 Announce Type: cross Abstract: Large language model agents increasingly operate in long-horizon environments where early mistakes can trigger cascading failures and trap agents in dead-end trajectories. Agents must therefore be able to proactively recover from… 34 arXiv — NLP / Computation & Language research 2d ago Locate, Judge, Read: Role-Specialized Tool Agents over a Knowledge-Point Index for Open-Domain Multimodal Document QA arXiv:2610.13128v1 Announce Type: cross Abstract: Question answering over large heterogeneous document collections requires first finding the right passages and then reading them, yet current retrieval-augmented agents give one model both kinds of tools and let it schedule… 38 arXiv — NLP / Computation & Language research 2d ago Les Mis\'erables Dialogue: A film-based network representation of social communication arXiv:2610.13148v1 Announce Type: cross Abstract: In this work, we revisit the classic Les Mis\'erables benchmark network from the perspective of social communication. Using the 1998 film adaptation of the novel, we construct the publicly available Les Mis\'erables Dialogue… 25 arXiv — NLP / Computation & Language research 2d ago JANUS: Enhancing Long-Horizon Autonomous Research with Co-Evolving World Models arXiv:2610.13194v1 Announce Type: cross Abstract: Long-horizon autonomous research has shown promise in accelerating scientific progress through sustained cycles of hypothesis generation, implementation, and validation. However, this Generate-Execute-Feedback paradigm relies on… 5 arXiv — NLP / Computation & Language research 2d ago What Do Audio-Language Judges of Generated Music Listen For? Four Probes with Controls from Expert Ratings arXiv:2610.13247v1 Announce Type: cross Abstract: Open audio-language models are used as judges of generated music: given a clip and its text prompt, the model rates the clip, and the judge is validated by how well its ratings correlate with expert ratings. The correlation does… 26 arXiv — NLP / Computation & Language research 2d ago Vision Transformers Learn Word Meaning from Images Alone arXiv:2610.13252v1 Announce Type: cross Abstract: Can a vision model learn what words mean from pixels alone? We show that the two largest DINOv3 vision transformers organize words rendered in images by word meaning, despite being pretrained using self-supervision on images… 5 arXiv — NLP / Computation & Language research 2d ago Beyond the Final Embedding: Retrieving Memories from Token-Level Evidence arXiv:2610.13277v1 Announce Type: cross Abstract: Memory-augmented assistants retrieve evidence from stored conversations and documents to answer queries. Most embedding-based retrievers compare single-vector representations of queries and memories, even when relevance depends… 24 arXiv — NLP / Computation & Language research 2d ago BoundaryEvo: Data-Model Co-Evolution at the Capability Boundary for Long-Chain Reasoning Distillation arXiv:2610.13285v1 Announce Type: cross Abstract: Distilling long-chain reasoning trajectories from large teacher models provides an effective way to improve the reasoning ability of small language models. However, existing methods typically select a fixed training set before… 16 arXiv — NLP / Computation & Language research 2d ago Taking Tokenization off the Host for Agentic LLM Serving arXiv:2610.13325v1 Announce Type: cross Abstract: Agentic workloads resend long contexts that barely change between calls. Prefix caching now skips most of their prefill, yet every request must still be tokenized in full before the cache can even be consulted. Tokenization, a… 5 arXiv — NLP / Computation & Language research 2d ago Exploring Attention Sinks in Text-to-Image Transformers from Diffusion and Autoregressive Models arXiv:2610.13337v1 Announce Type: cross Abstract: Attention sinks are tokens or positions that consistently receive disproportionate attention mass, often beyond what their semantic content would suggest. Despite extensive study in large language models, their behavior and… 38 arXiv — NLP / Computation & Language research 2d ago ProgramGym: Scaling Training Environments for Long-Horizon Program Reproduction Agents arXiv:2610.13395v1 Announce Type: cross Abstract: Coding agents are increasingly used to build programs from scratch as software engineers do rather than to resolve issues within a repository or to generate a repository from a given requirements document. However, scalable… 36 r/MachineLearning community 3d ago What's up with google scholar citations ? [D] Early-stage researcher, and yes, I get excited about people citing my work. I was browsing through arXiv for accepted NeurIPS papers, and I saw multiple papers citing my work. These papers have been there for months, but Google Scholar still has not updated its citations, and it… 5 r/MachineLearning community 5d ago [2610.08927] Can AI Agents Make Open-Ended Scientific Discovery? Evidence from Station Abstract: Recent AI systems have made rapid progress in scientific discovery when given well-defined metrics, but whether they can autonomously undertake open-ended scientific discovery remains unclear. We investigate AI's ability to tackle open-ended tasks in Station, an… 23 arXiv — Machine Learning research 5d ago Freeze the Decoder, Heal the Encoder: Parameter-Efficient Adaptation for SVD-Based KV-Cache Compression arXiv:2610.10552v1 Announce Type: new Abstract: Comparing parameter-efficient fine-tuning recipes under a single, shared learning rate is a common but flawed practice: when the arms being compared have very different trainable-parameter counts, a shared rate can simultaneously… 17 arXiv — Machine Learning research 5d ago SPERA: Spherical Prior EEG Foundation Model with Geometry- and Frequency-Aware Latent Prediction arXiv:2610.10571v1 Announce Type: new Abstract: Electroencephalography (EEG) provides a non-invasive measure of ongoing neural activity, but building general-purpose EEG models remains challenging due to the heterogeneity of subjects, devices, and electrode montages. Existing… 6 Page 4 of 10 · 500 articles ← Newer Older →
