Every paper checked — nothing hidden

All papers

Every paper checked in the week of 12–18 Oct 2026 · Small and efficient models — nothing is hidden. Brief papers first.

All2,430 In brief3 More (on-topic)455 Not relevant1,957 Not assessed6 Older27 Could not confirm6 Blogs with no paper16 All blogs19

Paper	Topic	Relevance
Where Words Begin and End The paper evaluates audio forced aligners and fine-tunes Whisper to predict human-aligned word boundaries across read, conversational, and telephone speech. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model compression, quantization, or serving efficiency.
BRIDGE: Selective Boundary Repair with Dependency Graph Evidence in Multi-Agent Systems The paper introduces BRIDGE, a runtime intervention framework that detects and repairs broken information handoffs across dependency graphs in multi-agent workflows. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address parameter reduction, distillation, or inference optimization.
Perturbation, Not Provenance: Why Activation Steering Does Not Make a Robust Text Watermark The paper tests activation steering as a text watermarking technique, finding that standard logit-based watermarking provides more robust detection against paraphrasing. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on watermarking security rather than model efficiency or compression.
Swiss4Arg: A Parallel Dataset for Multilingual Argument Mining across Swiss National Languages The paper introduces Swiss4Arg, a multilingual argument mining dataset based on official Swiss voting brochures across four national languages. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not study model compression, quantization, or efficient inference.
Text-Only vs. Image-Aware VLM Judges for Manga Translation Evaluation The paper evaluates whether providing page images to vision-language models improves the detection of errors in Japanese-English manga translation. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, distillation, or serving efficiency.
Agent-Reflex: Teaching Language Agents to Act Reflectively The paper introduces Agent-Reflex, a training framework designed to teach language agents how to reflect and recover from noisy environment feedback. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, pruning, or serving efficiency.
Fish Audio Drama 3 Technical Report The paper introduces Fish Audio Drama 3, an open-source text-to-speech model designed for multi-character dialogue, long-form synthesis, and iterative voice revision. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Presents a large 35B model, not model compression or small models.
Machine--human agreement in marking undergraduate assignments is specific to model, prompt and institution The paper examines machine grading on undergraduate essays across three universities, finding models compress score distributions and vary across institutions. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression or inference efficiency.
A Benchmark for Bangla Task-Oriented Dialogue Understanding The paper introduces BanglaTOD, a tri-lingual benchmark for task-oriented dialogue understanding covering Bangla, English, and romanized Banglish across nine service domains. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression, distillation, or efficient inference.
From Agents to Edges: Paired Optimization for Multi-Agent Collaboration The paper introduces an optimization method that jointly refines communication instructions between communicating agents to improve multi-agent collaboration. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression or inference efficiency.
Narrative Lookahead in LLMs: Event-Level Decodability, Predictive Advantage, and Steering The paper probes language model hidden states across generated stories to test whether models anticipate narrative events multiple steps ahead. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not study model compression, distillation, or serving.
Cheap, Consistent, Calibrated, but Biased? Typed Decision Models as Judges The paper evaluates typed decision models against standard language model judges to measure how emotional tone and biases affect their evaluation accuracy. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Studies decision model bias, not model compression or efficiency techniques.
Attacking Only Half the Data: Two-Sided Evaluation of AI-Text Detector Robustness Evaluates AI text detectors under attacks applied to both human and machine text, revealing high false-positive rates on edited human writing. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression or inference acceleration.
TRACESTEER: Trace Driven Activation Steering for Hallucination Mitigation in Diffusion Language Models Proposes dynamic activation steering using preceding denoising predictions to reduce hallucinations in diffusion language models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on hallucination mitigation rather than model compression.
SWE-MISBEHAVIOR: Benchmarking and Mitigating Boundary Violations in Software Coding Agents Introduces a benchmark evaluating coding agent misbehaviors across code generation, file management, and system environment integrity. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model efficiency, distillation, or serving.
PACT: A Pragmatic Prompting Framework for Expressive and Voice-Preserving Speech-to-Speech Translation Presents a pragmatic prompting framework to preserve speaker voice, emotion, and tone during speech-to-speech translation. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model compression, quantization, or serving.
Are We Testing Too Much? A Survey of Benchmark Compression for Efficient Evaluation of Large Language Models Surveys methods for compressing large language model benchmarks to reduce evaluation costs while maintaining accurate score estimates. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on benchmark dataset compression, not model compression or serving.
PAINT: A Framework for Multilingual Pain Representation from Medical Licensing Exams to Real-World Clinical Texts Presents a multilingual framework and dataset spanning four languages to evaluate clinical pain representations across exams and clinical notes. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression or inference efficiency.
LegalRewardBench: Benchmarking Reward Models for Legal Preference Evaluation Introduces a human-verified benchmark to evaluate how accurately reward models judge language model outputs on legal tasks. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression or inference efficiency.
Prompt or Policy? Optimizing Physician Slate Presentations with LLM User Simulators Develops a simulation framework using persona-guided models to optimize comparative doctor summary presentations for medical patients. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not investigate model efficiency, compression, or quantization.
Jev-Guard: Fast Routing and Auditing Agent Actions over Editable Policy Trees Introduces a low-latency guardrail model that routes incoming agent actions through editable policy trees for safety auditing. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on latency for guardrails, not model compression or efficiency methods.
Probing the Geometry of Color Representations in Multilingual Language Models Probes layer representations in multilingual language models to study whether internal color geometry aligns with human perception or language syntax. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression, efficiency, or serving.
Pin It on Anyone: Certified Targeted Displacement of Multi-Bit LLM Watermarks Without the Key Demonstrates an attack method that alters embedded multi-bit text watermarks without knowing the secret generation key. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model compression or inference efficiency.
Multi-Stream Residual Computation in Diffusion Language Models Equips diffusion language models with multiple residual streams and adaptive routing to separate visible context from masked token generation. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on efficiency, quantization, or model distillation.
Prompt-Injection Probes Learn the Conversation, Not Just the Injection Shows linear prompt-injection monitors overfit to conversation features and reduces their false alarms by adding matched harmless negative examples. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient serving.
Revisiting the Estimation of Unigram Surprisal in Computational Psycholinguistics Proposes estimating both contextual and unigram surprisal from the same language model to reduce estimation mismatch in reading time studies. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient serving.
Receiver Decides Agent-to-Agent Negotiations Studies agent-to-agent negotiations over money, finding that the receiving agent's characteristics primarily dictate the final transfer amounts. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not investigate model compression, distillation algorithms, or quantization.
Reliable Memory from Unstable Growth: Curating Self-Written Agent Playbooks with Randomized Experiments Presents a randomized experiment framework to test and curate self-written agent playbooks, preventing task failure caused by unverified lessons. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not study model compression, quantization, or efficient serving.
Estimating Surprisal from the Speech Signal Estimates surprisal directly from continuous speech signals using a speech language model and importance sampling over abstract linguistic units. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression, distillation, or efficient inference.
Copying Is Not Grounding: Training Faithful Long-Form RAG with Authored-Sentence Credit Identifies passage copying as a failure mode in long-form retrieval systems and introduces sentence-level credit assignment to encourage genuine grounding. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression or efficient serving techniques.
How Safe Is ChatGPT Health Advice? Evidence from Real User Conversations in Four Global South Countries Evaluates the safety of ChatGPT health advice using real user conversation logs across four Global South countries. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, pruning, or efficient inference.
The Last Mile of Coding Agents for Long-Document Tasks: An Empirical Study on Clinical Trial Protocol Digitization Introduces a benchmark evaluating how reliably software coding agents extract and digitize complex unstructured clinical trial protocol documents. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model compression or efficient serving.
Retrieval Disagreement as a Signal: Diagnosing and Steering Multilingual Dense Embedders Analyzes retrieval divergence across languages in multilingual dense embedders and introduces disagreement-guided steering to align shared-index search results. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model efficiency, distillation, or quantization.
How Reliable Are System-One Decisions in Medicine? A Comparative Study of Jev, Jev-like Models, and LLMs Evaluates fast, system-one decision models and language models across fifteen medical datasets, testing their accuracy, format robustness, and abstention awareness. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not investigate model compression, quantization, or distillation techniques.
Empathy Is Not the Scapegoat for Declines in Factuality and Reliability Examines whether model empathy degrades reliability, showing that warm behavior effects depend on tasks and training approaches rather than an inevitable trade-off. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not study model compression, distillation, or efficient inference.
CREATE: Creativity Evaluation of VLMs using the Visual Remote Associates Test This paper introduces a visual associative test benchmark to evaluate the lateral reasoning and creative association capabilities of vision-language models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient inference.
Decomposing and Predicting Annotation Disagreement in Harmful Content Across Languages This paper predicts human annotator disagreement on harmful content across multiple languages by extracting interpretable semantic question features with models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not involve model pruning, distillation, or quantization.
From Hindsight to Foresight: Dissecting Clinical Evidence Acquisition in Large Language Models This paper analyzes dynamic clinical evidence gathering in language models, identifying failures in evidence identification, updating, and diagnostic reasoning. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not cover model compression, distillation, or efficient serving.
Legal-R1: Agentic Retrieval for Evidence-Based Legal Reasoning This paper introduces a multi-agent retrieval framework that coordinates search across legal statutes and precedent cases for grounded legal reasoning. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression or efficient serving.
Breakdown of Conversational Involvement: A Joint Multi-Modal Analysis of Conversation Floors and F-formation Detection with Multiple Features This paper analyzes multi-person conversational involvement by jointly evaluating speaking floors and spatial formations from multimodal video features. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model efficiency or small language models.
Does Pretraining Teach Chemical Language Models Chemistry? This paper evaluates pretraining on chemical language models across 64 molecular datasets, finding that gains saturate below gradient-boosted tree baselines. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address small model compression, distillation, or efficient serving.
Bayesian Test-Time Inference of Task-Aligned Similarity from Weak Interactive Feedback This paper proposes a Bayesian method that infers task-aligned similarity metrics at test time using weak interactive feedback. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, distillation, or efficient serving.
Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models This paper presents a method to detect spoken code-switching directly from speech representations using language-selective hidden dimensions. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Examines speech encoder representations, not LLM compression or serving.
On the Monitorability of Natural Language Autoencoders: Identification vs Discrimination This paper uses referential communication games to analyze why natural language autoencoders fail to provide discriminative oversight of model activations. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Examines internal oversight mechanisms, not model compression or efficient serving.
Looking Complete Is Not Being Grounded: Evaluating LLM Sitreps Against Human-Authored Situation Reports This paper evaluates language-model-generated disaster situation reports against human-written reports using a domain-specific sixteen-slot information schema. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Studies evaluation quality, not model compression or inference efficiency.
Rubrics from the Task, Verdicts from Evidence: Pointwise Rubric Rewards with Tool-Augmented Judges This paper proposes a rubric-based reward model that derives criteria strictly from instructions and evaluates responses pointwise using tool assistance. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Deals with reward models and policy optimization, not model compression or serving.
SkillScaffold: Scaffolding Agentic Reinforcement Learning with Policy-Adaptive Skill Credit Assignment and Selective Injection This paper introduces a reinforcement learning scaffold that selectively injects textual skills into agents using low-cost utility estimation. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Addresses skill assignment in RL rather than model compression or efficient serving.
OmniCompass: A Holistic Benchmark for Omni-Modal Video Grounding and Understanding This paper introduces a benchmark to evaluate multimodal models on joint audio-visual temporal grounding, spatial grounding, and question answering. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Presents an evaluation benchmark rather than techniques for small or efficient models.
The Last Remote Sensing Model Built by Humans? Casting Any Earth Observation Task as Recursive Self-Improvement This paper frames Earth observation model development as an automated loop where coding agents build and iteratively refine models using verifiable harnesses. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient inference serving.
ClawLoop: Self-Improving Agents via Harness-Native Training Loop This paper introduces a training framework that enables harness-based software agents to self-improve without relying on external teacher models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on self-improving post-training loops, not model quantization or distillation.
Visualizing the World Model in an Agent's Value Function The paper uses counterfactual interventions to visualize and examine implicit environmental concepts learned inside a reinforcement learning agent's value function. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient serving.
Harness^2: Recursive Agent Harnessing for an Open World The authors propose a two-level recursive self-improvement framework to evolve and refine execution harnesses for open-world agents. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on model compression, quantization, or efficient serving.
Agentic Data Engineering for LLMs: System Design and a Controlled Empirical Study The authors present a framework where autonomous agents iteratively refine data engineering strategies to improve model training outcomes. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Focuses on training data selection rather than model compression.
GeoFix: Geometry Fixing for 4D Consistent Generation The authors introduce a framework that uses cross-view depth consistency as a single reward to improve 4D video generation geometry. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not investigate small models, distillation, or quantization.
ConicFlow: constrained Inference-time optimal control for flow matching models The paper introduces a receding-horizon optimal control algorithm for constrained sampling in flow matching generative models. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not focus on small models, distillation, or quantization.
MvFFN: Multi-view Floor plan Feed-forward Network for Unposed Wide-Baseline Panorama Layout Reconstruction The authors present a feed-forward network that aggregates local wall predictions to reconstruct floor plans from sparse unposed panoramas. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not study model compression, distillation, or efficient inference.
Which Metadata Matters for LLM Tool Selection in MCP? Evidence from Controlled Factor-Level Interventions The authors run controlled experiments showing how parameter schema differences in metadata alter language model tool selection. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Not related to small models, quantization, or compute efficiency.
Natural Code Transformation Confuses Agents in Vulnerability Analysis The study reports that natural code transformations confuse vulnerability analysis agents, proposing functional changes as a potential defensive strategy. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, quantization, or efficient inference.
DexFLEX: Contact-Aware Foundation Controller for Command-Guided Dexterity The authors present a foundation controller that converts motion drafts into contact-consistent joint commands for dexterous robotic hands. Preprint	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not target model quantization, distillation, or efficient inference serving.
Deep learning from a control vantage point The paper reviews deep learning architectures and training dynamics through the lens of continuous-time nonlinear control theory. Peer-reviewed	Small and efficient models via arxiv · 15 Oct, 06:17	Not relevant Does not address model compression, pruning, quantization, or serving optimizations.

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