News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — NLP / Computation & Language research 1d ago Principal Trait Analysis: Towards Deriving "Skills" in Human-AI Collaboration arXiv:2608.11460v1 Announce Type: new Abstract: Large Language Model-powered agents are increasingly used in the workplace via human-artificial intelligence (AI) collaboration. In this new era of work, it is important to understand the kinds of prompting traits that contribute… 34 arXiv — NLP / Computation & Language research 1d ago Group Alignment-Induced Sycophancy: A Two-Sided Evaluation of Steerable Pluralistic Alignment arXiv:2608.11528v1 Announce Type: new Abstract: Group alignment adapts a language model to a demographic group to produce responses that reflect the group's opinions, values, and preferences. Sycophancy, a well-documented by-product of alignment, causes the model to over-agree… 23 arXiv — NLP / Computation & Language research 1d ago On Weak Bisimilarities in CCSK arXiv:2608.11531v1 Announce Type: new Abstract: In the context of CCSK, a reversible extension of CCS, we study different notions of bisimilarity (strong/weak, forward-only/reversible) and highlight their differences and commonalities. In particular, for the weak reversible… 20 arXiv — NLP / Computation & Language research 1d ago CT-$\Delta$Bench: A Benchmark for Longitudinal 3D Medical Imaging Difference Reporting with Vision-Language Models arXiv:2608.11534v1 Announce Type: new Abstract: In medical imaging, the clinical value of Computed Tomography (CT) lies not only in depicting current disease status, but crucially in enabling longitudinal comparison of serial scans to determine disease evolution, a process that… 10 arXiv — NLP / Computation & Language research 1d ago Beyond Single-Turn Confidence: Trajectory-Adapted Uncertainty Quantification for LLM Agents arXiv:2608.11552v1 Announce Type: new Abstract: Uncertainty quantification (UQ) methods for language models are typically evaluated on single-turn outputs, where uncertainty is attached to one generated answer. For LLM agents, however, the unit of observation is an interactive… 4 arXiv — NLP / Computation & Language research 1d ago Reinforcing Step-level Reasoning for Effective Self-Correction in LLMs arXiv:2608.11573v1 Announce Type: new Abstract: Achieving effective self-correction, where models verify and correct their own mistakes, remains a fundamental challenge for large language models (LLMs). In this work, we propose Self-Fix Step-DPO (SFS-DPO), a reinforcement… 35 arXiv — NLP / Computation & Language research 1d ago Learning to Persuade Exposes How Easily LLMs Abandon Correct Beliefs arXiv:2608.11624v1 Announce Type: new Abstract: Persuasion is a core dynamic of natural language communication, shaping how large language models (LLMs) update beliefs, resolve disagreements, and reach decisions. As LLMs increasingly debate, advise, and think collaboratively… 13 arXiv — NLP / Computation & Language research 1d ago Easper: An Accessible ASR Pipeline for Language Documentation arXiv:2608.11629v1 Announce Type: new Abstract: Audio transcription is a critical bottleneck in language documentation. While multilingual Automatic Speech Recognition (ASR) models like Whisper offer solutions, field linguists often lack the expertise to utilise them. We present… 4 arXiv — NLP / Computation & Language research 1d ago Who Would You Vote For? Auditing Political Alignment in LLMs: An Italian Case-Study arXiv:2608.11649v1 Announce Type: new Abstract: As users increasingly turn to Large Language Models (LLMs) for information and advice on political matters, particularly during election periods, the political preferences expressed by these systems have become a matter of public… 36 arXiv — NLP / Computation & Language research 1d ago Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models arXiv:2608.11657v1 Announce Type: new Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into a continuous dynamical system within the macroscopic logit space. By… 23 arXiv — NLP / Computation & Language research 1d ago Hybrid-Policy Self-Editing for Composable Unstructured Knowledge Editing arXiv:2608.11660v1 Announce Type: new Abstract: Large language models (LLMs) achieve remarkable performance across natural language tasks, yet they are trained on static corpora and their knowledge quickly becomes outdated in a fast-changing world. This motivates knowledge… 5 arXiv — NLP / Computation & Language research 1d ago The Wording Effect: Quantifying Two-Way Drift in LLM Benchmark Performance arXiv:2608.11694v1 Announce Type: new Abstract: A benchmark score comes from a single phrasing of each problem. That single phrasing is treated as if it stood for the whole space of ways the same problem could be asked, but it does not. We show that rephrasing a problem while… 11 arXiv — NLP / Computation & Language research 1d ago When the API Speaks the Wrong Language: Revisiting Post-Training for Multilingual Tool Use arXiv:2608.11715v1 Announce Type: new Abstract: The reliability of Large Language Models (LLMs) for API calling degrades in multilingual settings. A common failure occurs when a model selects the correct tool but generates argument values in an inconsistent language, which we… 6 arXiv — NLP / Computation & Language research 1d ago Locating and Controlling Implicit Personalization in Large Language Models arXiv:2608.11735v1 Announce Type: new Abstract: Large language models (LLMs) often shift their outputs in response to implicit demographic cues even when users never state a demographic identity. Previous work has documented this behavior, but the connection between these… 8 arXiv — NLP / Computation & Language research 1d ago Ripple-Pivot Search: Active Parallel Decoding for Diffusion Large Language Models arXiv:2608.11742v1 Announce Type: new Abstract: Diffusion Large Language Models (dLLMs) have emerged as a competitive alternative to autoregressive language models, offering the potential for substantially faster inference through parallel decoding. Existing parallel decoding… 37 arXiv — NLP / Computation & Language research 1d ago LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification arXiv:2608.11753v1 Announce Type: new Abstract: Financial text is produced and interpreted within a market environment, yet financial text classifiers almost always receive text alone. We study whether financial time series are useful as an additional input on the task of… 33 arXiv — NLP / Computation & Language research 1d ago AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention arXiv:2608.11758v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine-tuning these models on downstream tasks often leads to catastrophic… 34 arXiv — NLP / Computation & Language research 1d ago Causal Structure is Inducible but Functionally Decoupled: The Routing/Readout Boundary of a Typed Mechanism Library arXiv:2608.11767v1 Announce Type: new Abstract: When a language model answers an interventional question, the computation it must perform depends on the type of evidence the query requires. We report a decoupling in how a transformer organizes causal knowledge: slot-by-type… 33 arXiv — NLP / Computation & Language research 1d ago Diagnosis Before Recovery: Turning Agent Failures into Selective Self-Correction arXiv:2608.11772v1 Announce Type: new Abstract: Self-correction is particularly useful when a failure constrains the next repair. Coding agents benefit from this property because compilers, tests, and execution traces turn many failures into typed recovery signals, but broad… 27 arXiv — NLP / Computation & Language research 1d ago Language-Conditional Dequantization: Recovering What Quantization Steals from Non-English Languages arXiv:2608.11786v1 Announce Type: new Abstract: Aggressive quantization disproportionately harms multilingual capability: in the sub-4B INT3 GPTQ regime, we measure 2-4x larger perplexity degradation on non-English languages than on English. We propose Language-Conditional… 28 arXiv — NLP / Computation & Language research 1d ago GRPO for Financial Advice Generation: Outperforming Commercial LLMs under CATE Evaluation arXiv:2608.11787v1 Announce Type: new Abstract: Generating actionable financial advice from business records demands that models integrate numerical reasoning, domain knowledge, and sound judgment, while avoiding recommendations that could harm the business. Direct supervision… 6 arXiv — NLP / Computation & Language research 1d ago TELLME: Test-Enhanced Learning for Language Model Enrichment arXiv:2608.11788v1 Announce Type: new Abstract: Continual pre-training (CPT) has been widely adopted as a method for domain adaptation in large language models. However, CPT has consistently been accompanied by challenges, such as the difficulty of acquiring large-scale… 16 arXiv — NLP / Computation & Language research 1d ago Hybrid Gated Attention arXiv:2608.11805v1 Announce Type: new Abstract: Gated attention is an effective approach to mitigate attention sinks and enhance the representational capacity of attention. To further extend its effectiveness-efficiency Pareto frontier, we propose a Hybrid Gated Attention (HyGA)… 38 arXiv — NLP / Computation & Language research 1d ago Located but Not Releasable: Silent Gate Inversion and Bounded Linear Release arXiv:2608.11822v1 Announce Type: new Abstract: A growing body of work reports that language models represent task-relevant latent structure that they fail to use. Whether such structure, once located, can be converted into behavior is a separate question that is rarely tested… 5 arXiv — NLP / Computation & Language research 1d ago When the Knowledge Base Becomes the Gold Standard: Measuring Resource-Shared Evaluation Loops in Entity-Level Machine Translation arXiv:2608.11843v1 Announce Type: new Abstract: The Seungjeongwon Ilgi, a UNESCO Memory of the World record, is only 37.4% translated, and the most conspicuous failure mode in automatic translation is the person name -- a misread name corrupts the historical fact rather than… 28 arXiv — NLP / Computation & Language research 1d ago Total Recall at What Cost? Benchmarking the Serving Cost of Agentic Memory Systems arXiv:2608.11879v1 Announce Type: new Abstract: Long-running conversational agents increasingly rely on a memory system to avoid resending the whole conversation each turn, yet how much that costs to serve has received little systematic benchmarking. We compare three memory… 15 arXiv — NLP / Computation & Language research 1d ago LazyTrain: Limited-resource Allocation toward Zero-waste Yield Optimization in Large Language Model Training arXiv:2608.11919v1 Announce Type: new Abstract: Training large language models on limited hardware is increasingly a scheduling problem across GPU compute, host memory, PCIe transfer, and storage bandwidth. Existing offloading systems reduce GPU residency, and MegaTrain shows… 19 arXiv — NLP / Computation & Language research 1d ago LODESTAR: Trustworthy Entropy Is Navigated, Not Merely Measured -- Reinforced Polarizer Keeps a Frozen LLM from Being Confidently Misled by the Wrong Evidence arXiv:2608.11922v1 Announce Type: new Abstract: Predictive-distribution entropy makes a strong selection rule in retrieval-augmented question answering: across five QA benchmarks, keeping the candidate answer that a frozen respondent LLM produces with the lowest answer-token… 8 arXiv — NLP / Computation & Language research 1d ago Spark-to-Paper: End-to-End Research Paper Generation as a Composable Skill arXiv:2608.11924v1 Announce Type: new Abstract: Turning a research idea into a complete paper requires more than text generation: the system must retrieve literature, design and execute experiments, revise claims according to evidence, produce publication-ready figures, and… 20 arXiv — NLP / Computation & Language research 1d ago Accuracy and Order Sensitivity Diverge Under Label-Free Strategies arXiv:2608.11947v1 Announce Type: new Abstract: Multiple-choice benchmarks are widely used to evaluate large language models, but MCQ scores conflate knowledge with sensitivity to option order, which makes them unreliable measures of model knowledge. In this paper, we test… 35 arXiv — NLP / Computation & Language research 1d ago Benchmarking Trustworthiness of SLMs: Pre-trained vs. Compressed arXiv:2608.11981v1 Announce Type: new Abstract: Small Language Models (SLMs) have emerged as a more efficient alternative to traditional Large Language Models (LLMs), offering promising potential in resource-constrained scenarios. Existing approaches to building SLMs typically… 34 arXiv — NLP / Computation & Language research 1d ago Asymptotic Risk Calibration for Selective Question Answering arXiv:2608.12008v1 Announce Type: new Abstract: Large language models (LLMs) may generate fluent but incorrect answers, making uncertainty quantification important for reliable question answering. However, heuristic uncertainty scores cannot perfectly distinguish correct… 22 arXiv — NLP / Computation & Language research 1d ago Poly-Dialectal Neural Machine Translation System for Bangla Regional Dialects arXiv:2608.12018v1 Announce Type: new Abstract: Regional dialectal variation poses a fundamental challenge to natural language processing (NLP) in Bangla, where over 240 million speakers communicate across diverse regional variants that diverge significantly from Standard… 20 arXiv — NLP / Computation & Language research 1d ago Preference Tree Optimization: Enhancing Goal-Oriented Dialogue with Look-Ahead Simulations arXiv:2608.12062v1 Announce Type: new Abstract: Developing dialogue systems capable of engaging in multi-turn, goal-oriented conversations remains a significant challenge, especially in specialized domains with limited data. This research proposes a novel framework called… 31 arXiv — NLP / Computation & Language research 1d ago Structuring the Space of Perspectives arXiv:2608.12113v1 Announce Type: new Abstract: The same event can be reported from different perspectives depending on the experiences, background, and beliefs of the writer or speaker. A variety of NLP areas engage with perspectives, spanning from text analysis to algorithm… 6 arXiv — NLP / Computation & Language research 1d ago QV-PIC: Query-Aware Visual Position-Independent Caching for Efficient RAG Serving arXiv:2608.12121v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) repeatedly prefills identical text chunks across queries, incurring redundant computations. Position-Independent Caching (PIC) mitigates it by reusing precomputed Key-Value (KV) across… 27 arXiv — NLP / Computation & Language research 1d ago SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges arXiv:2608.12129v1 Announce Type: new Abstract: While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations remain inherently limited in handling structured constraints and multi-hop… 29 arXiv — NLP / Computation & Language research 1d ago A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench arXiv:2608.12138v1 Announce Type: new Abstract: General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but such comparisons draw on a narrow set of systems and on benchmarks developed… 10 arXiv — NLP / Computation & Language research 1d ago Massive Activations in Hybrid Linear Attention Large Language Models: Pre-Attention Spikes and Inter-Spike Plateaus arXiv:2608.12149v1 Announce Type: new Abstract: We present the first systematic study of Massive activations (MAs) in layer-interleaved HLA LLMs and uncover two architecture-aligned morphologies: MAs consistently spike immediately before full attention layers, forming… 6 arXiv — NLP / Computation & Language research 1d ago Information Abundance Paradox: Long-Context Training Undermines Parametric Knowledge arXiv:2608.12218v1 Announce Type: new Abstract: Large language models are increasingly trained and deployed with long contexts that span documents, code repositories, and interaction histories. This scaling reflects the implicit assumption that training on longer contexts will… 32 arXiv — NLP / Computation & Language research 1d ago One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL arXiv:2608.12253v1 Announce Type: new Abstract: Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior. We show that this approach systematically fails to generalize, and trace the failure to… 21 arXiv — NLP / Computation & Language research 1d ago A Cascaded Unsupervised-Supervised NLP Pipeline for Detecting Accusatory Language in Public Procurement arXiv:2608.12269v1 Announce Type: new Abstract: Public procurement involves the allocation of substantial financial resources; therefore, continuous oversight through audits, controls, and monitoring mechanisms is essential. However, stakeholder comments and publicly available… 23 arXiv — NLP / Computation & Language research 1d ago Structural Silence: When AI Infrastructure Fails Speakers of Underrepresented Languages arXiv:2608.12278v1 Announce Type: new Abstract: Artificial intelligence tools for education and language support are increasingly framed as scalable responses to access gaps in under-resourced communities. Yet the infrastructure underlying these tools, including training… 15 arXiv — NLP / Computation & Language research 1d ago Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop arXiv:2608.11215v1 Announce Type: cross Abstract: Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase behaviour, stylised facts, and scaling with the number of agents $N$, not the… 12 arXiv — NLP / Computation & Language research 1d ago From Monolithic to Modular: Segment-level Automatic Prompt Optimization arXiv:2608.11219v1 Announce Type: cross Abstract: Automatic Prompt Optimization (APO) often rewrites prompts monolithically, which can improve one behavior while degrading others. We present SAPO, a segment-level APO method that decomposes prompts into role, context, tasks, and… 16 arXiv — NLP / Computation & Language research 1d ago Harnessing agent memory to build lifelong AI partners for materials scientists arXiv:2608.11224v1 Announce Type: cross Abstract: Materials research advances through accumulated experience - scripts that work, protocols that are trusted, warnings attached to failed calculations or experiments, and judgement that links a new question to an old result. This… 30 arXiv — NLP / Computation & Language research 1d ago BEST-KAG: Enhancing Question Answering of Building Engineering Standards with Multimodal Knowledge Graph Modeling and Large Language Model arXiv:2608.11244v1 Announce Type: cross Abstract: Construction standards are critical for building safety and sustainability. Existing standard application workflows rely on keyword-based document retrieval and manual cross-clause interpretation, which cannot reliably support… 9 arXiv — NLP / Computation & Language research 1d ago RevCRN: Reversible Analog Computation using Chemical Reaction Networks arXiv:2608.11362v1 Announce Type: cross Abstract: The computability of real numbers and functions using Turing Machines has been a central area of theoretical computer science since the mid-20th century. In the late 20th century, it was shown that chemical reactions can serve as… 28 arXiv — NLP / Computation & Language research 1d ago When Self-Consistency Backfires: Majority Vote Hurts the Majority of Hard Science Problems for Small LLMs arXiv:2608.11403v1 Announce Type: cross Abstract: Self-consistency (SC) via majority vote is a widely used way to spend inference-time compute: sample N chains of thought, return the plurality answer. On the full GPQA Diamond benchmark (198 graduate-level science questions),… 30 arXiv — NLP / Computation & Language research 1d ago Social Chain of Thought: A Multi-Agent Architecture Grounded in Medical Differential Diagnosis Methodology arXiv:2608.11420v1 Announce Type: cross Abstract: Medical diagnostic reasoning is a high-impact use case for LLMs that carries significant implications for the health and wellbeing of users. When OpenAI (2026) reports that more than 5% of ChatGPT messages globally are… 9 Page 7 of 10 · 500 articles ← Newer Older →
